Maria Flavia Mogos
email: maria.f.mogos@ntnu.no

Børge Sjøbakk
email: borge.sjobakk@sintef.no

Erlend Alfnes
email: erlend.alfnes@ntnu.no

A Structured Outsourcing Procedure

Keywords: Outsourcing, Production transfer, Operations strategy

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Many Western companies choose to transfer parts of their production to other actors in their supply chains. Such transfers are often denoted outsourcing or offshoring processes, depending on the ownership structure (internal or external) and target location (domestic or foreign) of the transfer [START_REF]Outsourcing Strategically for Sustainable Competitive Advantage[END_REF]. Outsourcing generally refers to the handover of responsibility for certain activities across organizational borders, whereas offshoring indicates that the responsibility is transferred to a subsidiary or supplier in a foreign location. Due to its many stated benefits, such as lower factors costs, access to new materials, distribution channels and technologies, as well as increased capacity to focus on core competences, outsourcing has been a very popular strategy in many industries [START_REF] Kinkel | Drivers and Antecedents of Manufacturing Offshoring and Backshoring: A German Perspective[END_REF]. Still, it is associated with substantial risk and may lead to increased costs and loss of business if it is not carried out carefully and in a systematic mannerreflecting the high complexity of such transfer processes [START_REF] Kinkel | Drivers and Antecedents of Manufacturing Offshoring and Backshoring: A German Perspective[END_REF].

Outsourcing of production entails a vast amount of decisions to be taken. Although several outsourcing frameworks and guidelines exist, only a few [e.g. [START_REF] Momme | An Outsourcing Framework: Action Research in the Heavy Industry Sector[END_REF][START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF]] describe all stages of the outsourcing process. These are typically rather general in their description of the activities that need to be carried out at the different stages. More detailed frameworks typically focus on the make-or-buy phase of the process, by e.g. discussing possible benefits and risks when outsourcing [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF], or they end before the physical transfer [START_REF] Fredriksson | Materials Supply and Production Outsourcing[END_REF]. Frameworks that address the production transfer (PT), i.e. the actual relocation of manufacturing of products or components between two production facilities (Sender and Receiver), either focus on specific parts of the PT [START_REF] Fredriksson | Materials Supply and Production Outsourcing[END_REF], or provide only a general overview of interdependent activities important for supply performance [START_REF] Momme | An Outsourcing Framework: Action Research in the Heavy Industry Sector[END_REF][START_REF] Madsen | Knowledge Transfer in Global Production[END_REF][START_REF] Zeng | Global Sourcing: Process and Design for Efficient Management[END_REF]. No comprehensive frameworks integrating all these aspects have been identified. Therefore, the purpose of this paper is to synthesize existing research on outsourcing processes into one structured outsourcing procedure. This can guide companies in carrying out outsourcing activities in a systematic manner. The procedure is discussed in light of an instrumental case study of two PTs between a Norwegian supplier of advanced maritime monitoring systems and one of its strategic suppliers within electronic manufacturing services (EMS).

Research Method

The structured outsourcing procedure is proposed on the basis of a thorough study of literature on production-, knowledge-, and technology-transfers, as well as more general literature on outsourcing, production start-up and ramp-up. When structuring the literature, the most comprehensive identified models and methods [START_REF] Momme | An Outsourcing Framework: Action Research in the Heavy Industry Sector[END_REF][START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF][START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF] were taken as a starting point. During the structuring of the literature a need to add, rearrange and adjust phases emerged -more or less resulting in the proposed procedure. However, an instrumental case study approach [START_REF] Baxter | Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers[END_REF] has been selected to test and accomplish it. This was designed as a single case study as the access to adequate empirical data was limited to one supplierbuyer relation; however, two PTs were followed to increase the research quality. The empirical data was collected through workshops and semi-structured interviews with key representatives from both case companies, e.g. quality managers, product developers, key account managers and process engineers.

Structuring Outsourcing

In broad terms the production outsourcing process can be divided into three parts: [START_REF]Outsourcing Strategically for Sustainable Competitive Advantage[END_REF] deciding what (if any) to outsource, (2) selecting and committing a supplier, and (3) transferring the production. Each of these contains a number of activities that a company needs to go through during an outsourcing process. These are briefly described and summarized below. IDs are assigned to the activities, in order to link them to the suggested outsourcing procedure at the end of the section.

The Outsourcing Decision

In describing the outsourcing decision, a framework by Kremic et al. [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF] is adopted. This depicts typical elements of the outsourcing decision, and shows where motivators, benefits, risks and other factors are typically encountered. The first step is to consider outsourcing in the first place. Here, the sender's motivation for outsourcing is weighed against general risks and benefits. According to [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF] (a combination of) three major categories of motivation drives outsourcing: cost, strategy, and politics. The sender should have a conscious attitude towards these (A1). For instance, the outcome of outsourcing is often more successful if the decision is based on strategic considerations rather than solely on financial problems [START_REF] Brandes | Outsourcing-success or Failure?: Findings from Five Case Studies[END_REF]. Further, the sender should analyze whether common benefits and risks of outsourcing either strengthen or weaken the decision (A2). Although it is not explicitly stated in the literature, we suggest documenting (A3) and communicating (A4) the resulting outsourcing policy internally. Next, the sender should identify (A5), evaluate (A6) and select (A7) what, if any, to outsource based on strategic-, financial-, functional-and environmental factors of each candidate and on the outsourcing policy [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF]. When production is outsourced, Semini et al. [START_REF] Semini | What to Offshore, What to Produce at Home? A Methodology[END_REF] suggest careful attention to aspects such as logistics, equipment utilization, proximity to product development and intellectual property.

Supplier Selection

When the company has selected which functions, products or processes it should outsource, the next stage is to select a target supplier and location for the transfer. Here, a fourstage supplier selection process by Cousins et al. [START_REF] Cousins | Strategic Supply Management: Principles, Theories and Practice[END_REF] is adopted. First, suppliers are prequalified (A8). Prequalification criteria will vary between companies and industries; however, suppliers' manufacturing capabilities and financial viability will usually be assessed. Often, companies keep a record of prequalified suppliers, enabling them to skip this phase. Otherwise, information about suppliers needs to be collected and evaluated. Next, the company should agree on measurement criteria (A9) that are specific to the product under consideration (e.g. unit price, lead time, supplier flexibility). Third, relevant information about suppliers should be gathered (A10), for example through requests for proposal or quotation. This information is used to make a selection in the fourth phase (A11). Danilovic and Winroth [START_REF] Danilovic | A Tentative Framework for Analyzing Integration in Collaborative Manufacturing Network Settings: A Case Study[END_REF] argue that no matter how hard management strives to have a high level of integration in collaborative networks, the integration must be supported by legal agreements (A12). Draft agreements would often need to be designed for each case. Examples of issues that need to be included are forms of decision making, risk allocation, security issues and renegotiation/termination rules [START_REF] Danilovic | A Tentative Framework for Analyzing Integration in Collaborative Manufacturing Network Settings: A Case Study[END_REF]. As will be evident in the next section, the contract may need to specify responsibilities before, during and after the transfer.

Production Transfer

Finally, when the receiving supplier has been selected the PT can commence. Based on [START_REF] Madsen | Knowledge Transfer in Global Production[END_REF], a PT process consists of four phases: the preparation for transfer, the physical transfer of equipment and inventories, the production start-up at Receiver, and the steady state. The Steady State starts after there has been reached a full-scale and stable production, at targeted levels of cost and quality [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. Each of the PT related activities identified in the literature has been assigned to one of these four phases (Table 1).

Table 1. Overview of the studied production transfers and their main activities Outsourcing policy: A1. Identify the amount of cost-driven, strategy-driven and politically-driven outsourcing [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF][START_REF] Brandes | Outsourcing-success or Failure?: Findings from Five Case Studies[END_REF]. A2. Analyze whether benefits and risks will strengthen or weaken the decision to outsource [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF]. A3. Establish policy document. A4. Communicate the company's outsourcing policy to employees. Outsourcing candidate selection: A5. Identify possible candidates for outsourcing (functions, products or processes) [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF]. A6. Evaluate identified candidates [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF][START_REF] Semini | What to Offshore, What to Produce at Home? A Methodology[END_REF]. A7. Select candidate(s) [START_REF] Kremic | Outsourcing Decision Support: A Survey of Benefits, Risks, and Decision Factors[END_REF]. Supplier selection: A8. Prequalify suppliers [START_REF] Cousins | Strategic Supply Management: Principles, Theories and Practice[END_REF]. A9. Agree on measurement criteria [START_REF] Cousins | Strategic Supply Management: Principles, Theories and Practice[END_REF]. A10. Obtain relevant information [START_REF] Cousins | Strategic Supply Management: Principles, Theories and Practice[END_REF]. A11. Make selection [START_REF] Cousins | Strategic Supply Management: Principles, Theories and Practice[END_REF] A12. Contract negotiation [START_REF] Danilovic | A Tentative Framework for Analyzing Integration in Collaborative Manufacturing Network Settings: A Case Study[END_REF].

Transfer preparation: A13. Establish Project team [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF][START_REF] Madsen | Knowledge Transfer in Global Production[END_REF]. A14. Kick-off meeting [START_REF] Dudley | Successful Technology Transfer Requires more than Technical Knowhow[END_REF] A15. Establish other teams [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF][START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. A16. Sign formal agreement [START_REF] Danilovic | A Tentative Framework for Analyzing Integration in Collaborative Manufacturing Network Settings: A Case Study[END_REF][START_REF] Zhu | Outsourcing: A Strategic Move: The Process and the Ingredients for Success[END_REF]. A17. Plan as Stepwise Transfer during low demand season (if possible) [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF]. A18. Ensure interaction with Receiver. Higher uncertainty, higher requirements [START_REF] Stock | A Typology of Project-level Technology Transfer Processes[END_REF]. A19. Develop training plan [START_REF] Andre | Towards a Framework for Transferring Technology Knowledge Between Facilities[END_REF]. A20. Create transfer register. Include Transfer plans and checklist, Change Control procedure, etc. [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF] A21.Evaluate Receiver's preparedness (premises, equipment., support services) [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF]. A22.Perform Transfer Risk Assessment. Implement measures [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF]. A23.Problem solving upgrading recalibration test of production system [START_REF] Madsen | Knowledge Transfer in Global Production[END_REF][START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF].

A24. Define Engineering Change process [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF] A25. Train Receiver's personnel [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF][START_REF] Andre | Towards a Framework for Transferring Technology Knowledge Between Facilities[END_REF]. A26. Update/ create documentation with Receiver [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF][START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF][START_REF] Andre | Towards a Framework for Transferring Technology Knowledge Between Facilities[END_REF]. A27. Improve Receiver's performance [START_REF] Modi | Supplier Development: Improving Supplier Performance through Knowledge Transfer[END_REF] A28. Update Planning & Control system [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF]. A29. Develop Communication plan [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF]. A30. Transfer information [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF]. A31. Receiver reviews info. and finds gaps [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF]. A32. Ensure joint info. sharing platform [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. A33. Establish relations to sub-suppliers [START_REF] Aaboen | The Relationship Development Aspect of Production Transfer[END_REF] A34. Verify preparations [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF]. Physical Transfer: A35. Transfer production equipment [START_REF] Madsen | Knowledge Transfer in Global Production[END_REF]. A36. Send personnel to Receiver [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. A37. Install and test production equipment [START_REF] Madsen | Knowledge Transfer in Global Production[END_REF]. Production Start-up: A38. Sender temporary transfers personnel [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. A39. Set up experimental line [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. A40. Involve all affected personnel [START_REF] Madsen | Knowledge Transfer in Global Production[END_REF]. A41. Qualify component vendors [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. A42. Decide when to transfer responsibility to order raw material to Receiver [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF]. A43.Adapt processes to a new environment [START_REF] Grant | Adapting Manufacturing Processes for International Transfer[END_REF]. A44. Problem solving on parts/materials [START_REF] Madsen | Knowledge Transfer in Global Production[END_REF]. A45. Verify production [START_REF] Hilletofth | Challenges with Industralization in a Supply Chain Network: A Supplier Perspective[END_REF]. A46. Continuously monitor performance. Consider shutdown when lower than targets to solve problems [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. Implement measures [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF][START_REF] Mccormack | Managing Risk in your Organization with the SCOR Methodology[END_REF]. A47. Adapt docs and Plan. & Control syst. [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF]. A48. Conduct post-transfer audit. Evaluate transfer [START_REF] Zhu | Outsourcing: A Strategic Move: The Process and the Ingredients for Success[END_REF][START_REF] Hilletofth | Challenges with Industralization in a Supply Chain Network: A Supplier Perspective[END_REF]. A49. Gen. sum. report (lessons learned, etc.) [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF]. Production Steady State: A50. Continuously monitor and improve production [START_REF] Madsen | Knowledge Transfer in Global Production[END_REF]. Consider maintaining experimental line [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF] Apart from the Physical Transfer, a PT consists of three additional types of transfers: knowledge transfer (KT) (of tacit knowledge), administrative transfer (AT) (of explicit/codified knowledge), and supply chain transfer (SCT) (by establishing relations to vendors of materials) [25]. It is important to ensure all these types of transfers during a PT. In addition, transfer parties will have to perform certain project administrative activities, such as establishing a PT organization and manage the PT project [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF].

The transfer preparation phase includes the most identified activities. Here, KT activities are mainly related to the training (A25) and involvement of Receiver personnel in the preparation of documentation, the systems, and of the production equipment and processes (A26). In addition, it might be necessary to implement KT activities for performance improvement at Receiver, such as six sigma or lean [START_REF] Modi | Supplier Development: Improving Supplier Performance through Knowledge Transfer[END_REF] (A27). AT activities are related to e.g. updating of planning and control systems with data based on the estimated lead times and other performance indicators for the PT [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF] (A28), and the transfer of the updated information to Receiver (drawings, materials planning method, packaging procedures, etc.) (A30). SCT primarily concerns a possible transfer of suppliers to the Receiver (A33). Examples of project management (PM) activities are kick-off meeting (A14), signing of formal agreements (A16), and generating a transfer register with plans, flow diagrams, instructions and control procedures (accessible to both parties and up-to-date) (A20). The physical transfer mainly involves transfer of production equipment (A35), installation and testing of equipment (A36), but also certain KT by temporary transferring personnel from Sender to Receiver (A36) to provide support and report back to Sender [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. Such a transfer can also take place during start-up (A38). Other KT activities during start-up imply setting up an experimental line for learning and for testing of performance improvement solutions at the Receiver (A39), and involving all the affected personnel along the process (A40). An AT task for the Receiver is to adapt documentation and systems to their own planning environment (A47). SCT activities during start-up are mainly related to qualification of component vendors (A41) and the decision about when to transfer the responsibility to order raw material to the Receiver (A42). As a PM activity, a summary report (A50) should be generated and stored in the transfer register.

Discussion and Conclusions

The empirical data collected during the case research is summarized in Table 2.

As seen in Table 2, Sender and Receiver had a series of challenges with the two PTs that might have been reduced by some of the actions from Table 1. For instance, communicating the company's outsourcing policy internally (A4) and organizing a kick-off meeting where the reason for the PT is clarified (A14), could have increased the Product Team's motivation to share essential information with the Receiver in Case A [START_REF] Dudley | Successful Technology Transfer Requires more than Technical Knowhow[END_REF]. The PT parties should have constituted a project team (A14), with PT managers and other members from all the affected disciplines and with clear roles [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. Moreover, as stated by [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF], PTs should be managed by help of a PM plan based on risk management principles (A20). Hence, all the activities with potentially negative consequences (e.g. transferring the test equipment to Receiver) should have been identified together with experienced personnel and measures should have been implemented (i.e. risk management) (A22). Further, some authors state that PTs, to the extent possible, should be planned as 'stepwise' transfers (A17) instead of 'clear-cut', as in Case A. Production at Sender should be gradually decreased as volumes increase at Receiver. Thus, in case of unexpected demand or major production disruptions during Start-up, one would have a secondary source of supply at the Sender [START_REF] Fredriksson | A Structured Procedure for Materials Planning During Production Transfer[END_REF]. Further, parties had several communication issues in both Case A and B. Thus, by preparing a communication plan (with e.g. points of contact and their roles) (A29), they could have minimized these challenges. This plan should be included in the PT register along with the PT plan and other tools, such as activities checklists, a change control system, and a flow diagram [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF][START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. Moreover, the register should be continuously updated and an easily accessible to both parties (A20). Finally, at the end of the Start-up in Case A, Sender could have conducted a post-transfer audit, comparing the pre-and post-outsourcing costs [START_REF] Zhu | Outsourcing: A Strategic Move: The Process and the Ingredients for Success[END_REF] and evaluating whether the Steady-state had been achieved and whether the production should be relocated to other manufacturer or not (A48). In ad-Table 2. Overview of the studied production transfers and their main activities Completed transfer: Case A Ongoing transfer: Case B Transfer object: Acoustic sensor. Mature product. High volumes. Not too complex. Little IP. Original location: Sender's production facility in Norway. Before, Sender had been producing the sensors and assembled them with housings and electronics from two different suppliers. New location: After transfer, Receiver assembles tests and delivers final products to Sender. Receiver is expected to reduce unit cost over time.

Outsourcing policy: Combination of cost and strategy. Need to reduce cost; aim to be a 'technology company' rather than manufacturing company.

Outsourcing candidate selection: High volume product that requires higher efficiency and less competence than the Sender has. Supplier selection: The Receiver was prequalified and used to deliver electronics for the product. Preparations: Parties had no kick-off meeting. Key personnel in the Product Team, Sales, and Test were little involved in the preparations. Product Team was little informed about the reason for the transfer and their motivation to support Receiver was low. It had been unclear who was responsible for what at Sender and a transfer plan and risk assessment had not been prepared and conducted before transfer. Initially, it was decided that all test equipment would be moved from Sender to Receiver. When Product Team found this out, they realized that the Sender would not be able to run spot-checks, losing the control over the quality of their deliveries. Moreover, initially, Sender was to manufacture the product until Easter and Receiver everything after that (clean-cut). This turned out to be unrealistic. [KT:] Receiver participated in VSM at Sender and sent 3 operators to learn the process at Sender. [SCT:] Sender's original suppliers of housings and electronics were transferred to Receiver. Physical Transfer: Sender copied their test equipment and transferred the copy to Receiver. Start-up: Receiver experienced that several of their process improvement suggestions were rejected without a clear justification and the latest ones even turned out to be futile. During a workshop (April '15), the Product Team revealed, to the Receiver's surprise, their plans to update the product to a new version. Finally, Sender was unaware if the transfer had been profitable or not, but they said that the start-up was long with high scrap rates and stock levels. dition, Receiver's performance should be monitored along the entire PT and measures should be implemented (A50) [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF]. With respect to Case B, several authors stress the importance of a formal agreement (A12, A16) between parties, signed as early as possible during Preparations. The agreement should include each party's responsibilities along the process (e.g. who bears the cost of obsolete material), and desired performance targets (e.g. yield) [START_REF] Terwiesch | International Product Transfer and Production Ramp-up: A Case Study from the Data Storage Industry[END_REF]. Further, to effectively manage engineering changes, parties could also define the change control process (A24) during Preparations, and they could create a flow diagram of the PT with necessary decisions gates [START_REF]World Health Organization: Expert Committee on Specifications for Pharmaceutical Preparations[END_REF]. For instance, before starting with the continuous manufacturing, the production should have passed a verification gate (A45). Finally, with higher uncertainty of the PT (i.e. novelty, complexity, and tacit knowledge) there are higher requirements of interaction between parties (A18). For Case B, the For Case B, the assembly of product B was novel for the Receiver; the product version was an innovation, and it had a high amount of uncodified knowledge. Thus, parties could have invested more in information management systems (e.g. a common IT platform) and could have drawn advantage from the domestic proximity by having regular and more frequent meetings with the Receiver [START_REF] Hilletofth | Challenges with Industralization in a Supply Chain Network: A Supplier Perspective[END_REF].

In this study, existing research on outsourcing processes is synthesized into one structured outsourcing procedure, comprising the outsourcing decision, the supplier selection, and the PT stage. We argue that one of the strengths this procedure is providing a detailed overview of the PT specific activities, which are often overseen in earlier outsourcing procedures despite their impact on final performance results. The proposed procedure can guide practitioners in conducting production outsourcing processes in a systematic manner. Nevertheless, it should be validated in different manufacturing contexts and adapted to different types of production outsourcing. The authors objective for the future is to configure and validate a phase model comprising activities from the current procedure, decision gates, suggested disciplines for each activity, as well as appropriate methods and tools.

  Same as in Case A. Their experience with product A was partly decisive. Preparations: The transfer started in Sept. '14, with a kick-off. Sender asked Receiver to secure material from sub-suppliers without any formal agreement. A significant amount of this material became obsolete because of BOM changes, and the financial consequences were unsettled for a long time. The transfer was planned with partially overlapped product development at Sender and process development at Receiver. Often, BOM and other product design changes came too late (e.g. during continuous production instead of the Pilot phase). 4 BOM changes were sent after Receiver had ordered material. Moreover, Sender had problems with own change control system that did not allow purchasing materials for prototypes before design-freeze. Thus, many changes were unrecorded until Product Developer started to collect them in a common excel-file. [KT:] At the time of the workshop in April '15, the production had been transferred from Receiver's Development department to Manuf.

	Transfer object: Signal converter. New version
	of existing product. More complex than Product
	A.
	Original location: The same as in Case A. For
	previous version, Sender installed PCBs from Re-
	ceiver in cabinets from one supplier, and power
	supply and wiring from another supplier. Sender
	tested the final products.
	New location: Same Receiver as in Case A. Af-
	ter transfer, Receiver installs electronics includ-
	ing own PCBs in cabinets. Sender still tests final
	products.
	Outsourcing policy: Same as in Case A.
	Outsourcing candidate selection: Product
	was selected due to the upcoming new version,
	'now was the time'. Key components were already
	outsourced.
	Supplier selection: No personnel from Receiver were transferred for
	training at Sender.
	Receiver appreciated having one contact person
	at Sender (Product Developer) whereas Sender's
	Prod. Developer felt that it had been challeng-
	ing to know whom to contact at Receiver. She
	had also experienced that two contacts at the
	Receiver had different BOM revisions. [SCT:]
	Sender's original supplier of cabinets was trans-
	ferred to Receiver. Later on, Sender may replace
	them by its own subsidiary in a low-cost country.
	Physical Transfer: None.
	Start-up:

Acknowledgements This research has been conducted with support from the research project SoundChain funded by The Research Council of Norway. The authors would like to thank the project participants for providing valuable empirical data.


Sayyed Shoaib-Ul-Hasan
email: sayyed.shoaibulhasan@polimi.it

Marco Macchi
email: marco.macchi@polimi.it

Alessandro Pozzetti
email: alessandro.pozzetti@polimi.it

Pursuit of Responsiveness in SMEs Through Dynamic Allocation of Flexible Workers: A Simulation Study

Keywords: Responsiveness, Simulation, Demand variability, SMEs, Flexibility

The aim of this research is to study production responsiveness in Small and Medium Enterprises (SMEs) in Italy. Responsiveness is considered as the ability of a production system to achieve its goals in the presence of disturbances. The main issue this research tries to address is "how responsiveness can be achieved in production environments facing recurring uncertain disturbances in demand?" This research is particularly focused on the "worker flexibility" as a lever to achieve responsiveness. In this regard, alternative control logics for decision-making, regarding use of workers with varying levels of flexibility, have been evaluated through simulation for their potential impact on production responsiveness. It is found that, contrary to general belief, higher flexibility does not always guarantee higher responsiveness; it is the right level of flexibility combined with the proper decision-making logic which leads to higher production performance in the face of recurring uncertain disturbances.

Introduction

Mass customization has emerged as a new business strategy to respond to customers' demand for high product variety. It has brought many challenges for manufacturing industry, particularly for small and medium-sized enterprises (SMEs) operating in global market. Mass customization is characterized by high demand variability, which adversely impacts production performance [START_REF] Bozarth | The Impact of Supply Chain Complexity on Manufacturing Plant Performance[END_REF]. In fact, mass customization production companies face swings in demand and thus vary in their capacity utilization [START_REF] Holweg | Successful Build-to-order Strategies Start with the Customer[END_REF][START_REF] Hu | Product Variety and Manufacturing Complexity in Assembly Systems and Supply Chains[END_REF]. Demand variability has been recognized as having the broadest negative impact on plant performance and it represents a pure measure of dynamic complexity [START_REF] Molleman | Functional Flexibility and Team Performance[END_REF]. If not properly and timely addressed, demand variability may cause productivity loss as well as human errors with negative impacts on production performance [START_REF] Norman | Worker Assignment in Cellular Manufacturing Considering Technical and Human Skills[END_REF]. Furthermore, uncertain demand disturbances cause snow-ball effects such as delays on customer orders, logistics errors and high level of work-in-progress inventories [START_REF] Jimenez | The Pursuit of Responsiveness in Production Environments: From Flexibility to Reconfigurability[END_REF].

However, in order to compete in the global market, companies need to respond to such uncertain disturbances in demand quickly and effectively. Therefore, many companies are pursuing responsiveness as one of their main performance priorities and are looking for ways to achieve higher responsiveness in their production environments [START_REF] Pil | Linking Product Variety to Order-fulfillment Strategies[END_REF].

In line with contingency theory, the required level of responsiveness that every company needs is different and depends on their individual business strategies [START_REF] Gunasekaran | Creating the Customer-responsive Supply Chain: A Reconciliation of Concepts[END_REF][START_REF] Roh | Implementation of a Responsive Supply Chain Strategy in Global Complexity[END_REF]. Hence, the basis for competitiveness must be designed individually according to the company's own particular circumstances [START_REF] Pil | Linking Product Variety to Order-fulfillment Strategies[END_REF] which may vary according to country, industry, company size and/or other contingencies. In this regard, this research particularly focuses on uncertain demand disturbances in SMEs and the use of "worker flexibility" as a lever to achieve responsiveness. Thus, the paper tries to answer the following question: How SMEs can properly use their worker flexibility to achieve responsiveness to recurring uncertain disturbances in demand?

In this regard, to evaluate the impact of different alternative control logics regarding use of worker flexibility, a simulation study has been designed in collaboration with an Italian SME. For simulation purposes "Plant Simulation" software is used. Simulation is performed based on real production data and with real system constraints. Performance for alternative control logics is measured based on their ability to meet the average monthly demand across different product models. Simulation results for alternative control logics are analyzed and compared to identify the best solution for adaptive decision-making in the face of recurring uncertain disturbances in demand.

Worker Flexibility

The purpose of this study is to investigate the use of worker flexibility to address demand variability in a production layout made of assembly cells. Previously, in literature, different terms have been used to conceptualize "worker flexibility", such as multi-tasking [START_REF] Ruiz-Torres | Impact of Worker and Shop Flexibility on Assembly Cells[END_REF] and multi-functionality [START_REF] Uskonen | The Price of Responsiveness: Cost Analysis of Change Orders in Make-to-order Manufacturing[END_REF]. This conceptualization of worker flexibility implies that the workers have the capacity to perform more than one task. However, researchers in group technology argue that multi-tasking alone is not enough, in fact workers should be able to perform different tasks in different areas (or call it cells) according to the needs. In this regard [START_REF] Yazici | Influence of Flexibilities on Manufacturing Cells for Faster Delivery Using Simulation[END_REF], for example, argues that "labor flexibility is the ability to assign varying number of operators as needed to perform different tasks. This requires training of operators to perform various tasks as well as their flexible assignment between different cells". In a similar vein [START_REF] Zhong | RFID-enabled Real-time Manufacturing Execution System for Mass-customization Production[END_REF] argued that "the presence of worker flexibility is characterized by cross-trained workers and the ability of workers to move between cells". Therefore, we can conclude that worker flexibility has two dimensions: i) capacity to perform more than one task, i.e. multi-tasking ii) dynamic allocation between tasks, i.e. flexible assignment. In this research, these dimensions are conceptualized as following: multitasking (worker characteristic) is the capacity of workers to carry out tasks within their assembly cell as well as tasks required in other cells; dynamic (re)allocation between tasks (system characteristic) is the possibility, by the system management, to be able to (re)allocate workers among different cells according to needed tasks, thanks to their capacity of multitasking.

Case Company

This research has been performed in collaboration with an Italian SME. The company produces slicers and offers more than 55 different models of slicers. These slicers are divided into two macro families which are i) vertical slicers, and ii) inclined slicers. This division arises from the fact that the assembly operation of a vertical blade differs from that of an inclined blade (which is a critical operation and requires different skill set). These macro families have further sub families (micro families). In total there are 8 micro families of slicers each consisting of different product models. Fig. 1 shows the product family tree and how different products belong to the micro and macro families. The company organizes production according to assemble-to-order (ATO) strategy where individual components are produced and stocked beforehand. Final assembly is performed only when the actual orders arrive. The assembly of all slicers consists of five phases which are 1) Preassembly operations on the motor; 2) Preassembly operations on the blade; 3) Assembly of the motor and related components on the base; 4) Assembly of the blade on the base and its fitting with the motor; 5) Calibration of blade. The precedence of assembly phases is shown in Fig 2 .   Phase 1 and 2 consist of pre-assembly operations and are performed by low skill workers (LSW). LSW are workers with no specialization and they lack skills to perform final assembly phases. Therefore, the final assembly phases 3, 4 and 5 are performed only by the high skill workers (HSW) who are well trained and experienced. However, workers can perform assembly operations only within their own macro family. This constraint is put by the management to achieve high quality in assembly as assembly of both macro families require different Fig. 2. Precedence of assembly phases skill set and experience. This constraint is particularly important for this study as we try to understand its impacts on responsiveness when evaluating different alternatives. The sub division of high skill and low skill workers in an assembly cell is given as in table 1. Company uses 8 different assembly cells, where each cell is dedicated to a particular micro-family. The demand for different product models varies during the year and company needs to make some adjustments in its existing configuration at shop floor to meet the new demand. Company is looking for other better ways and capabilities to achieve a quick and effective reconfiguration in response to recurring uncertain disturbances in demand. In this regard, different alternative control logics for adaptive decision-making regarding reconfiguration are being considered which are discussed in in next section.

Control Logics for Adaptive Decision-making and Simulation Design

Control logics for adaptive decision-making are built on dynamic allocation and multi-tasking. Regarding dynamic allocation, the company has two options: shift the product/workload from mother-cell to a host-cell or move the workers from an offering-cell to a cell-in-need to meet the demand in that cell. Furthermore, regarding mul-titasking there are also two options: train workers to perform assembly operations within one macro-family (basic level multi-tasking) or train workers to perform assembly operations on both macro families (high level multitasking). Thus, there are four alternatives that can be evaluated through simulation as shown in Fig. 3. Correspondingly, two are the decisions that will be compared: i) the dynamic allocation of workers versus the dynamic allocation of workload between the cells; ii) the level of worker flexibility, with the purpose to understand if capacity to perform tasks on both macro families is actually better or not, despite this would lead to a loss of efficiency due to less experience of workers on some tasks. The efficiency value for worker is 100% if he performs assembly operation within his family, 90% when he performs operation on other family but within the same macro family, and 80% if he performs operations on family outside his own macro family. These values are validated by the company manager who collaborated in this research. He has served for several departments before assuming his current position. From Fig. 3, it is apparent that there are four quadrants and each quadrant has its own control logic which is designed according to the requirements of the production context in SMEs: it should be easily and quickly manageable. To verify the effect on performances, the models for all control logics are developed. Because of space constraint in this paper, we discuss in detail only the control logic and the model for dynamic allocation of workers with basic level multi-tasking (DAFW). In order to develop such logic, the following procedure is adopted at the end of every week: a) calculate the current amount of workload present in each cell (workload as a function of number of slicers allocated to each cell); b) calculate the production capacity as function of the number of high skill and low skill workers currently working within each cell; c) calculate the remaining number of working days from the current moment till the end of the month; d) with the information provided by 'b' and 'c', calculate the number of slicers that can be assembled by the end of the month in each cell; e) if this quantity calculated in step 'd' is greater than that specified in step 'a', start an iterative process from step 'b' and calculate the production capacity with one worker less than the previous condition; f) after second iteration, for any cell, if the quantity calculated in step 'd' is still greater than that specified in step 'a', that cell becomes an offering-cell and makes available its worker to the whole macro-family, i.e. worker can be used to meet the capacity requirement of a cellin-need within the same macro-family. In fact, if a cell is generating a delay of one week with respect to the end of the month (it is the cell-in-need), then it can receive a worker from another cell (depending on availability of worker) to increase its production capacity.

Overall, it is worth pointing out that when a cell has a worker to offer to the system, the worker leaves only in the case when there is need in another cell. Similarly, if a cell is expected to mature late delivery and one or more of its workers are allocated to other cells-in-need, the cell will get its workers back regardless of the situation in host cells. With these constraints the quality and workers performance loss (due to inefficiency when working outside of their micro-family) becomes less influential, while the cells with delayed delivery can get extra workers from offering-cells to increase their production capacity. In order develop a mathematical model for the control logic explained so far, we need to calculate the total number of needed hours, based on current workload for both HSW and LSW, in each cell, then comparing it with total number of remaining hours, both for HSW and LSW, in each cell till the end of month. In this regard, following indexes are used: Xi: the total number of slicers of micro-family i currently present in the cell Ti: the total average time for the production of a slicer of the micro-family i αi: the share of total average time spent by the final assembly operations 1-αi: the share of total average time spent by the pre-assembly operations glr: the remaining number of working days until the end of month nli: the number of low skill workers present in cell belonging to micro-family i nhi: the number of high skill workers present in cell belonging to micro-family i xhi: the number of remaining working hours for HSW till the end of month xli: the number of remaining working hours for LSW till the end of month wh: number of daily working hours available for both HSW and LSW We can calculate the number of hours needed by HSW and LSW in a cell to complete the current workload of micro-family i by following equations:

h -HS i = X i * T i * α i (1) h -LS i = X i * T i * (1 -α i ) (2)
h -HS and h -LS are used as benchmarks that allow system to figure out if a cell is able to yield a worker or is in need of a worker by comparing it with the total number of hours remaining, for both HSW and LSW in a cell till the end of the month. Remaining working hours can be calculated by the following equations respectively:

xh i = nh i * wh * glr (3)
xl i = nl i * wh * glr (4)
xhi and xli are the total working hours calculated by adding up the hours that each worker can work from the current moment till the end of the month. If xhi > h -HS i and/or xli > h -LS i , the equation 3 and 4 are executed again with one less worker. After second iteration again if xhi > h -HS i and/or xli > h -LS i , then the cell yields, respectively, a HSW or LSW that can be used in a cell where xhi < h -HS i and/or xli < h -LS i (provided delay is more than one week, otherwise no action is required).

Simulation, Analysis and Results

Simulation is performed for all four control logics, where, monthly throughput is measured for each micro-family. All control logics used same resources and same types of demand patterns. In fact, simulation is performed using real production data and with real system constraints. Summary of findings is shown in table 2 where alternative control logics for adaptive decision-making are compared for their ability to meet monthly demand of each micro-family (calculated as the ratio between average monthly throughput and average monthly demand for each micro-family). It can be seen from the table that without any allocation logic the production system can meet only less than 90% of the monthly demand of microfamilies 7 and 8; while with dynamic allocation of flexible workers (DAFW) the production system can meet more than 99% of the overall demand for each microfamily with same resources. Overall, DAFW with basic level multi-tasking yields the highest performance when compared with other control logics. Interestingly, our results show that, with high flexibility (i.e. by high level multitasking) the overall performance is decreased due to worker efficiency losses when performing operations on products other than their own macro-family.

Conclusion

This paper addressed uncertain demand disturbances and the achievement of production responsiveness in an environment made of assembly cells with workers as main resource. In this paper, simulation is used to evaluate alternative control logics for decision-making regarding recurring uncertain disturbances in demand. These control logics include i) dynamic allocation between cells (workload versus workers), ii) different levels of worker flexibility (basic versus high level multitasking). Our simulation study shows that dynamic allocation of flexible workers leads to higher responsiveness to disturbances in demand when compared with dynamic allocation of workload. Furthermore, we found that higher flexibility does not always guarantee higher performance. In fact, it is the right level of flexibility combined with the proper decision-making logic which leads to higher performance. Therefore, a careful analysis of requisite flexibility and the proper decision logic is important to achieve higher responsiveness. Our results are clearly contingent to type of production environment and the type and nature of disturbance; therefore, in the future it will be interesting to study variants of such type of control logics in different environments subject to different demand patterns.

Fig. 1 .

 1 Fig. 1. Product family tree

Fig. 3 .

 3 Fig. 3. Alternative control logics

Table 1 .

 1 Subdivision of workers within a cell

	Total number of Number of Number of
	workers in a cell	LSW	HSW
	2	1	1
	3	1	2
	4	2	2
	5	2	3

Table 2 .

 2 Comparative results for different control logics

	DAFW DAFW (HF) DAWL DAWL (HF) No allocation
	Family 1 99.96%	99.95%	97.90%	98.94%	97.41%
	Family 2 99.91%	99.36%	97.49%	98.95%	93.52%
	Family 3 99.55%	99.94%	98.97%	99.88%	98.97%
	Family 4 99.89%	99.94%	99.92%	100.00%	99.92%
	Family 5 99.80%	99.91%	99.01%	99.64%	98.76%
	Family 6 99.84%	99.86%	98.57%	94.35%	92.69%
	Family 7 99.87%	99.78%	99.33%	99.48%	89.60%
	Family 8 98.58%	98.58%	94.41%	98.05%	89.67%
	Overall 99.68%	99.66%	98.20%	98.66%	95.07%

Acknowledgments. This paper is produced as part of the EMJD Programme European Doctorate in Industrial Management (EDIM) funded by the European Commission, Erasmus Mundus Action 1.


Erlend Alfnes
email: erlend.alfnes@ntnu.no

Maria Kollberg Thomassen

Marthe Bostad

Comparing Techniques for Selecting Automation Technology

Keywords: Operations strategy, Automation, technology acquisition, Justification techniques

scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Manufacturing companies are forced to look for progressive automation technologies to keep their market share and maintain competitive [START_REF] Chan | Investment Appraisal Techniques for Advanced Manufacturing Technology (AMT): A Literature Review[END_REF][START_REF] Sambasivarao | A Decision Support System for Selection And Justification of Advanced Manufacturing Technologies[END_REF]. The capability of the companies competitiveness is essential for their survival [START_REF] Chan | Investment Appraisal Techniques for Advanced Manufacturing Technology (AMT): A Literature Review[END_REF][START_REF] Säfsten | The Content and Process of Automation Strategies[END_REF]. Automation technology has been the development key driver of processes in manufacturing plants since it entered the manufacturing industry [START_REF] Ordoobadi | Development of a Justification Tool for Advanced Manufacturing Technologies: System-Wide Benefits Value Analysis[END_REF][START_REF] Jovane | Present and Future of Flexible Automation: Towards New Paradigms[END_REF]. Implementing an automatic system can result in cost savings within production or increased efficiency, productivity and competitiveness [START_REF] Frohm | The Industry's View on Automation in Manufacturing[END_REF][START_REF] Groover | Automation, Production Systems, and Computer-Integrated Manufacturing[END_REF]. However, the introduction of automation technology will need time to achieve successive implementation [START_REF] Frohm | Levels of Automation in Production Systems[END_REF][START_REF] Meredith | Managing Factory Automation Projects[END_REF]. It is also important to be aware that automation can bring problems and failures and not necessarily immediate success [START_REF] Lindström | Aligning Manufacturing Strategy And Levels Of Automation: A Case Study[END_REF]. Additionally, Frohm [START_REF] Frohm | Levels of Automation in Production Systems[END_REF] states that increasing level of automation in unforeseen production situations can be related to production disturbances, while Duncheon [START_REF] Duncheon | Product Miniaturization Requires Automation-But With a Strategy[END_REF] list challenging cases like innovative products or products with short life cycle because of the uncertainty related to such production. The development of manufacturing systems entail large investments, which will require justification of the decisions that are to be made [START_REF] Sambasivarao | A Decision Support System for Selection And Justification of Advanced Manufacturing Technologies[END_REF][START_REF] Ordoobadi | Development of a Justification Tool for Advanced Manufacturing Technologies: System-Wide Benefits Value Analysis[END_REF][START_REF] Parsaei | A Justification Methodology For Automated Manufacturing Technologies[END_REF]. The literature consists of many justification techniques for the acquisition of automation technology, but the use of such techniques in industry is limited. The existing techniques are criticised for being too time consuming, or not user friendly, or for putting too much weight on the financial aspects, or for a lack of sufficient support to the decision maker in certain phases of the selection process [START_REF] Säfsten | The Content and Process of Automation Strategies[END_REF][START_REF] Baines | An Integrated Process for Forming Manufacturing Technology Acquisition Decisions[END_REF][START_REF] Durrani | Managing the Technology Acquisition Process[END_REF][START_REF] Granlund | Managing Automation Development Projects: A Comparison of Industrial Needs and Existing Theoretical Support[END_REF]. There is a need to verify the usefulness of such methods in the industry [START_REF] Small | Economic and Strategic Justification of AMT inferences from Industrial Practices[END_REF][START_REF] Shehabuddeen | From Theory to Practice: Challenges in Operationalising a Technology Selection Framework[END_REF].

The purpose of this paper is identify two justification techniques that support the main phases of an automation technology selection process, to test these techniques in a case, and evaluate their usefulness in practice. The main contribution is a set of criteria for evaluating justification techniques, and insights about the usefulness of two justification techniques in industry.

The paper is organised as follows. First, the methodological approach is discussed. Next, the most common justification techniques is reviewed. Two techniques are applied and evaluated in a case study. Finally, conclusions are presented together with suggestions for further work.

Methodological Considerations

This study is based upon a literature review and a case study of an automation selection and acquisition process. The purpose of the literature was to investigate the main criteria for evaluating and prioritising justification techniques. Based on the review, a set of criteria for evaluating justification techniques is developed. An single case study approach was chosen to ensure enough detail and in-depth insights about actual use of justification techniques in industry. The case company was selected because they have an ongoing manufacturing system development project that include decisions regarding several processes and technologies that require a systematic evaluation and justification. Case company data was collected in several iterations over a year. Most of the data were collected in workshops with case company representatives. Interviews and discussions with key personnel were carried out combined with plant visits.

Theoretical Discussion

Chan et al. [START_REF] Chan | Investment Appraisal Techniques for Advanced Manufacturing Technology (AMT): A Literature Review[END_REF] classifies justification techniques into the three groups; strategic, economic or analytic approach which can be used unaided or combined. The combination of strategic and economic approaches is a common combination since the strategic approach has direct tie to the goals of the firm, and the possibility of overlooking the economical and tactical impacts gets covered by the economic approach [START_REF] Chan | Investment Appraisal Techniques for Advanced Manufacturing Technology (AMT): A Literature Review[END_REF]. The economic approach is based on an evaluation of the economic aspects and can contribute to the final decision of choosing an automation technology [START_REF] Chan | Investment Appraisal Techniques for Advanced Manufacturing Technology (AMT): A Literature Review[END_REF]. The strategic approach involve analysis of competitive advantage, business objectives, research and development, and technical importance [START_REF] Chan | Investment Appraisal Techniques for Advanced Manufacturing Technology (AMT): A Literature Review[END_REF][START_REF] Small | Economic and Strategic Justification of AMT inferences from Industrial Practices[END_REF].

Justification Techniques

The main phases that should be supported by a justification technique is technology strategy, analysis of operations competences and requirements, analysis of potential technologies, investments analysis, and implementation policy analysis [START_REF] Thomassen | A Strategic Approach for Automation Technology Initiatives Selection[END_REF]. The main justification techniques and their support for different phases are listed in Table 1.

Table 1. Justification techniques and the main phases they support.

References Strategic Operations Technology

Investment

Imple- mentation Baines [13] X X X X Chan et al. [1] X X X X X Chuang et al. [19] X X X Durrani et al. [14] X X X Efstathiades et al. [20]
X X X X X Farooq and O'Brien [START_REF] Farooq | Technology Selection Framework for Integrating Manufacturing Within A Supply Chain[END_REF] X X Iakymenko [START_REF] Iakymenko | An Approach for Evaluating the Appropriateness of Automation in Manufacturing Processes with Increasing Product Mix[END_REF] X X X Raafat [START_REF] Raafat | A Comprehensive Bibliography on Justification of Advanced Manufacturing Systems[END_REF] X Sambasivarao and Deshmukh [START_REF] Sambasivarao | A Decision Support System for Selection And Justification of Advanced Manufacturing Technologies[END_REF] X X Shehabuddeen et al. [START_REF] Shehabuddeen | From Theory to Practice: Challenges in Operationalising a Technology Selection Framework[END_REF] X X Thomassen et al. [START_REF] Thomassen | A Strategic Approach for Automation Technology Initiatives Selection[END_REF] X X X X X Torkkeli and Tuominen [START_REF] Torkkeli | The Contribution of Technology Selection to Core Competencies[END_REF] X X X

Criteria for Selecting Justification Techniques

An utilisation of justification techniques can contribute to evaluate important areas when acquiring automation technology [START_REF] Chan | Investment Appraisal Techniques for Advanced Manufacturing Technology (AMT): A Literature Review[END_REF][START_REF] Granlund | Managing Automation Development Projects: A Comparison of Industrial Needs and Existing Theoretical Support[END_REF][START_REF] Suresh | Justifying Multimachine Systems: An Integrated Strategic Approach[END_REF][START_REF] Gregory | Technology Management: A Process Approach[END_REF]. The important areas can vary in the different techniques, which depends on their aim of support. However, it is essential that a technique contributes with enough support in the acquisition process [START_REF] Torkkeli | The Contribution of Technology Selection to Core Competencies[END_REF], as well as evaluating the necessary area for the particular process [START_REF] Säfsten | The Content and Process of Automation Strategies[END_REF][START_REF] Baines | An Integrated Process for Forming Manufacturing Technology Acquisition Decisions[END_REF][START_REF] Durrani | Managing the Technology Acquisition Process[END_REF][START_REF] Torkkeli | The Contribution of Technology Selection to Core Competencies[END_REF]. For a justification technique to be supportive in an acquisition of automation technology, it has to be applicable and well explained [START_REF] Baines | An Integrated Process for Forming Manufacturing Technology Acquisition Decisions[END_REF][START_REF] Durrani | Managing the Technology Acquisition Process[END_REF][START_REF] Thomassen | A Strategic Approach for Automation Technology Initiatives Selection[END_REF]. Such technique will be easy to follow and prevent unnecessary use of time or expertise. Effective techniques will reduce the time and work load for a practitioner. Additionally, production processes with special challenges will benefit justification techniques with the possibility of modifying evaluation areas [START_REF] Shehabuddeen | From Theory to Practice: Challenges in Operationalising a Technology Selection Framework[END_REF][START_REF] Torkkeli | The Contribution of Technology Selection to Core Competencies[END_REF]. The most important criteria for evaluating the usefulness of justification techniques is listed in Table 2. Order is placed for the selected automation technology on the assembly process 05. 2017

Automation technology for the assembly process is implemented 07.2019

The production line is fully automated in the manufacturing company

The Evaluation of Technologies

The automation technology offers received from three different suppliers were evaluated with the two justification techniques in the case study. The first offer, technology alternative 1, consists of robots processing and transferring one product at time between the stations. The second offer, technology alternative 2, consists of transporting pallets with multiple products. In addition, the input is handled by a robot and navigated with a camera solution. The last offer evaluated, technology alternative 3, consists of an input with a blister and transports multiple products with pallets. The practitioner picked out three parts of the assembly process for evaluation, which were the three most important parts in the assembly process to be supported by techniques. Three processes in assembly were selected for evaluation, 1) materialhandling between work station, 2) feeding components to a station, and 3) gluing and control. The more strategic evaluation performed by the APROS method suggested that the company should select technology 1. The second justification technique gave scores with very small deviations (technology 1: 6,1, technology 2: 5,7, and technology 3: 6,4). The final decision was therefore to go for technology 1, with robots processing and transferring one product at time between the stations.

Discussion

The two justification techniques point out different solutions, but the differences between the results of technologies are not so different with a closer look. The results are in close race in both of the techniques for each process, which make all results from the justification techniques valuable. The evaluation of the usefulness of the justification techniques is summarized in Table 5.

Conclusion

This paper reviews justification techniques and test how such methods perform in practice. The main contribution is a set of criteria for evaluating justification techniques, and some insights about the usefulness of two justification techniques in industry. The application of two techniques in a case study showed that both techniques has strengths and weaknesses, and their applicability depend on the purpose and manufacturing environment for a technology acquisition process.

Further work should be done to test justification techniques and evaluate their usefulness in case companies that has different technology challenges and manufacturing environments.

Table 3 .

 3 Milestones in the automation project.

	Date	Activity
	12. 2015	Project start in the production department
	01. 2016	Tender sent for the assembly process
	02. 2016	Meetings held with potential suppliers for the assembly process
	03. 2016	Offers received from suppliers on the assembly process
	04. 2016	Supplier selected for an automation technology in the assembly process
	06. 2016

Table 4 .

 4 Results of the technology evaluation.

	Part of the process	Selected alternative in the first technique	Selected alternative in the second technique
	Intern transport	Technology alternative 1	Technology alternative 3
	Input	Technology alternative 2	Technology alternative 3
	Glue applying and control Technology alternative 1	Technology alternative 3

Table 5 .

 5 Evaluation of the techniques based on evaluation criteria.Both justification techniques provides good support for a automation technology acquisition process. The APROS approach is suited to guide the complete acquisition process from establishing strategy to investment in technology. The APROS methodology supports multiple parts of the acquisition process, and this makes it possible to use the technique in different areas dependent on the practitioner's requirements. It is visual, highly effective, easy to understand, and evaluate important areas of the technologies. However, it should include earlier experience with the suppliers and their reputation, and does not explain the cost calculations well enough. The technology selection framework, only supports the core selection process in the acquisition of an automation technology. It is based on a detailed scoring model and is a more thorough justification technique. However, it is difficult to understand at first. It does not explain the meaning of the scores in the model, which made the practitioners insecure of how to understand the score scale. The cost calculations are not explained well enough. The choice of method therefor depends on the type of acquisition process a company is performing, and how well the technology strategy, competences, and supplier relations are established in the company.

				The tech.
	Category	Criteria	APROS	selection
				framework
	Ease of perfor-	Effective in execution	X	X
	mance	Applicable	X	X
		Well explained	X
	Covers necessary	Include the important areas	X	X
	areas	Possibility to include additional areas		X
		Guides one part of the acquisition process		X
		Guides multiple parts of the acquisition process	X
		Exclude the practitioner's "gut" feeling		X
	Type of approach Combination of strategic and economic approach	X	X
		Evaluate with a visualising model	X
		Evaluate with a scoring model		X

Acknowledgements. This research is supported by the Research Council of Norway through the research projects EFFEKT and Manufacturing Network 4.0.

Case Study

The case company is within the aerospace and defense industry. The company wants to automate a production line for medium and large caliber ammunition, where many operations currently are performed manually and several processes are very challenging to automate. Two justification methods were selected for testing. The APROS (Automation Project Selection) method [START_REF] Thomassen | A Strategic Approach for Automation Technology Initiatives Selection[END_REF] was chosen because it support all phases of a technology acquisition process. The technology selection framework [START_REF] Shehabuddeen | From Theory to Practice: Challenges in Operationalising a Technology Selection Framework[END_REF] has a more limited scope, but were selected because it provides a set of scoring models that enables a thorough evaluation of a certain technology.

The Automation Project

The planned production line to be transformed into fully automated production line consists of stamping tracer and explosives (semi-automated), assembly (semi-automated), marking (fully automated) and packing (manual process). A mapping of the processes has shown that the assembly process seems to be the most challenging to automate, and a plan with milestones has been to automate the assembly process, Table 3.


Denis Wiesse
email: denis.wiesse@gmail.com

Christoph Roser
email: christoph.roser@hochschule-karlsruhe.de

Supermarkets vs. FIFO Lanes: A Comparison of Work-in-Process Inventories and Delivery Performance

Keywords: Inventory reduction, FIFO, Supermarket, Pull, Delivery Performance, WIP

Pull production is a key element for a lean manufacturing system. In pull production, buffer inventories between two processes can be implemented either through a FIFO lane as part of a kanban loop, or through a supermarket, in which case the value stream is split into two different kanban loops. This paper compares the usage of FIFO lanes and supermarkets with respect to the work-in-process inventory needed to achieve a similar delivery performance. The results clearly show that there is only a minor difference in inventory between the usage of FIFO lanes and supermarkets.

Introduction

Pull production is a key element for a lean manufacturing system. Kanban systems are commonly used to implement pull production. A pull system can consist of multiple kanban loops, each of which can include multiple processes along the value stream. The buffer inventory between two processes can be implemented either through a FIFO lane as part of a kanban loop, or through a supermarket, in which case the value stream is split into two different kanban loops.

Buffer inventories are necessary to decouple fluctuations between processes, which may stem from technical problems, cycle-time variations, unsteady material delivery, and many other reasons. The larger the buffer, the better the decoupling of fluctuations.

Yet, buffer inventories also cause significant costs. Industry usually calculates the cost due to the bound capital, sometimes also including storage and handling cost. What is usually not included is the delay of information through the material flow (e.g., detecting flawed parts too late), obsolescence cost, deterioration over time, etc. [START_REF] Richardson | Control Your Costs Then Cut Them[END_REF]. One of the key insights in lean manufacturing is to realize the significance of these inventory related costs and to pursue inventory reduction as part of the continuous improvement process.

When establishing a pull production, between each pair of sequential processes the designers have the option to add a FIFO lane as part of a bigger kanban loop, or to add a supermarket and split the flow into two kanban loops (see Fig. 1 below for the example used within this analysis). There are no fixed rules on when to use a FIFO and when to use a supermarket, although there are recommended guidelines [START_REF] Roser | Guidelines for the Selection of FIFO Lanes and Supermarkets for Kanban-Based Pull Systems -When to Use a FIFO and When to Use a Supermarket[END_REF]. In general, it is recommended to use a FIFO lane, which is much easier to manage, unless there are compelling reasons to go for a supermarket.

This paper compares the usage of FIFO and supermarket with respect to both work-in-process and delivery performance. The goal is to determine if a supermarket or a FIFO requires less work-in-process inventory for the same delivery performance. Is it better for inventory to have a supermarket or a FIFO between processes? This paper is based on a master thesis by one of the authors, supervised by the other author [START_REF] Wiesse | Analyse des Umlaufbestandes von Verbrauchssteuerungen in Abhängigkeit von der Nutzung von Supermärkten und FiFo-Strecken[END_REF]. To the best of our knowledge such a comparison has not yet been undertaken before. However, before we go into the details of the analysis, we first need to define the terms as used within this paper.

Definition of Push and Pull

While the term pull is used almost everywhere in lean manufacturing, the definition of pull is often quite different. It is only agreed that pull is the opposite of push. Powell and Arica recently surveyed the literature and found around 30 definitions in production management, supply chain management, and project management [START_REF] Powell | To Pull or Not to Pull: A Concept Lost in Translation?[END_REF]. Within this paper we follow the, in our view, most compelling definition by Hopp and Spearman "A pull production system is one that explicitly limits the amount of work in process that can be in the system. By default, this implies that a push production system is one that has no explicit limit on the amount of work in process that can be in the system" [START_REF] Hopp | To pull or not to pull: what is the question?[END_REF].

Definition of FIFO Lanes

A FIFO lane stands for First-In, First-Out. This automatically gives the first part of a definition, which requires that the parts leave in the same sequence as they arrive [START_REF] Marchwinski | Lean Lexicon: A Graphical Glossary for Lean Thinkers[END_REF]. However, since the FIFO lane is part of a pull system, it needs to incorporate the definition of pull from above and needs to have an upper limit on inventory. This brings us to our own definition of a FIFO lane:"A FIFO lane is an inventory where the parts leave in the same sequence as they arrive. There is a limit to the maximum inventory. If the FIFO lane is full, the receding process stops".

Definition of Supermarkets

A supermarket differs from a FIFO lane in that the material flow and the information flow splits. In a FIFO lane, the material automatically includes the information on what the material is. If material is removed from a supermarket, the information on the part goes back to the beginning of the kanban loop to replenish the part. This information is the kanban. A supermarket consists of multiple parallel FIFO lanes, one for each material type that is handled by the supermarket. As with the FIFO lane, the supermarket has an upper limit on the number of parts, although this is usually maintained through the number of kanban in circulation and not implemented separately. This leads us to our definition of supermarket "A supermarket is an inventory where the parts are stored separately by type. The parts by type leave in the same sequence as they arrive. When a part leaves, information is sent back along the value stream to replenish the part".

Definition of Work-in-Process Inventory

The definition of work in process is rather straightforward."Work in process (WIP) is the amount of material -measured in pieces, or by weight, volume, or value -for one part type or for multiple part types combined for a certain section of the value stream".

Depending on the situation, this may or may not include the supermarket inventory. For our purposes, we do include the supermarket inventory to get a reasonable comparison between a system with a FIFO and a system with a supermarket. For pull systems, this quantity has to be limited. In kanban systems, it is limited through the number of kanban [START_REF] Karmarkar | Kanban Systems[END_REF].

Definition of Delivery Performance

Delivery performance aims to measure the reliability of satisfying customer orders, both quantity-wise and timewise (i.e., in full on time) [START_REF] Rao | Delivery Performance Measurement in an Integrated Supply Chain Management: Case Study in Batteries Manufacturing Firm[END_REF]. Disagreement exists in industry if a too-early delivery is counted as good or not, which tolerances are allowed around the scheduled delivery date, and if the scheduled delivery date is the first date requested by the customer or the date agreed on between customer and supplier. For our purposes, we define delivery performance as follows: "Percentage of the customer orders that can be fulfilled on time and in full".

Analysis

For the analysis, a simulation environment was used. This allows for an easy gathering of data and comparison of different systems.

Analyzed System

For a stringent comparison, we analyzed a simple system consisting only of two processes, P1 and P2, and a single product variant. Two different systems were compared, where either a single kanban loop includes both processes with a FIFO in between, or the system is split into two different kanban loops. This is shown in Fig. 1 below as a) and b) respectively. For the diagrams, we used standard value stream mapping notation as introduced by Rother and Shook [START_REF] Rother | Learning to See: Value Stream Mapping to Add Value and Eliminate Muda[END_REF].

Intuitively, a supermarket has more inventory than a FIFO lane. However, having a longer replenishment time in a) requires one large supermarket at the end, whereas the two separate loops in b) each have a shorter replenishment time and hence both supermarkets require less material for a similar delivery performance. In the following, we will call a) a single-loop system, and b) a double-loop system.

System Settings

The systems in Fig. 1 have been compared using different settings of cycle times and customer demand to represent a variety of different situations that may be expected in industry. Since the durations are all relative to each other, no time units are required, although for simulation purposes, minutes were used. Table 1 gives an overview of the tested systems. We examined systems that had both equal cycle times and unequal cycle times. Additional systems were tested in the original master thesis with similar results [START_REF] Wiesse | Analyse des Umlaufbestandes von Verbrauchssteuerungen in Abhängigkeit von der Nutzung von Supermärkten und FiFo-Strecken[END_REF]. The systems have been simulated using the commercial Simul8 software package. All times were exponentially distributed. The duration of each simulation exceeded 8,000 parts, excluding a warm-up period of 300 parts. Each simula-tion was repeated at least 51 times to verify the accuracy of the results using confidence intervals.

All systems have been simulated using a wide range for the number of kanban both for a single-loop and a double-loop system to determine the relation between the WIP and the delivery performance. For example, the single-loop system 1 has been simulated with any number of kanban cards between 1 and 40 in combination with any number of FIFO capacity between 1 and 40. In total, 1,600 simulations have been repeated 51 times, each merely for the single-loop system with equal cycle times and a slow customer takt. The double-loop system 1 has been simulated with any number of kanban cards between 1 and 30 for each loop (i.e., a total of 900 simulations, all of them repeated 51 times for accuracy).

Similar simulations were performed for system 2 both for the single-loop and double-loop system. Simulations of additional systems can be found in [START_REF] Wiesse | Analyse des Umlaufbestandes von Verbrauchssteuerungen in Abhängigkeit von der Nutzung von Supermärkten und FiFo-Strecken[END_REF]. In all cases, the best combination of WIP and delivery performance were determined, as well as the expected results, using a standard kanban formula. Overall, in excess of 300,000 simulations using weeks of computation time were used to derive the data below.

Analysis Results

System 1 -Equal Cycle Time

All combinations of kanban cards between 1 and 40, and FIFO capacity between 1 and 40, for the single loop as well as all combinations of number of kanban cards for both loops between 1 and 30 have been simulated. Both the delivery performance and the WIP have been measured for each simulation. Fig. 2 shows the best combination with minimal WIP for any delivery performance between 0 and 100% for both the single-loop and the double-loop system. As expected, a higher WIP through a higher number of kanban and FIFO capacity improves the delivery performance. The relation is not linear, and a disproportionally larger inventory is needed to achieve a near-perfect delivery performance. The optimal combination of WIP and delivery performance for both the single-loop and the double-loop system looks very similar. Additional statistical analysis, however, confirms that the two curves are indeed statistically significant different for delivery performances in excess of 30% [START_REF] Wiesse | Analyse des Umlaufbestandes von Verbrauchssteuerungen in Abhängigkeit von der Nutzung von Supermärkten und FiFo-Strecken[END_REF]. This analysis shows that the single-loop system a) in Fig. 1 requires less WIP to achieve the same delivery performance as the alternative double-loop system b).

System 2 -Unequal Cycle Time

The second system is similar to system 1, except that the second process P2 now has a faster mean cycle time of nine time units instead of ten time units. Fig. 3 shows again the best combination of WIP and delivery performance for the single-loop and double-loop system. Again, the single-loop system requires statistically significant less WIP for the same delivery performance compared to the double-loop system. In all simulated systems (and additional systems found in [START_REF] Wiesse | Analyse des Umlaufbestandes von Verbrauchssteuerungen in Abhängigkeit von der Nutzung von Supermärkten und FiFo-Strecken[END_REF]), the single-loop system requires less WIP for the same delivery performance. These results are statistically significant for delivery performances above 50%. This means that since most companies have a delivery performance above 40%, these results are statistically significant.

The single-loop system is able to "work ahead" more during times of low demand. Fig. 4 shows the material distribution for times with low or no demand.

In the single-loop systems, all kanban would eventually end up with material in the supermarket, and all WIP would be concentrated in the supermarket. If demand would pick up again, the single-loop system would be theoretically able to deliver products equivalent to all kanban cards immediately. The exact allocation of the WIP depends on the number of kanban cards in each loop. Hence, the double-loop system would theoretically be able to deliver only the material equivalent to the last kanban loop. If the demand would be higher, material from the intermediate supermarket would first have to pass through process P2.

Since delivery performance is a benefit but WIP is a cost, a system that has better delivery performance for the same WIP (or the same delivery performance for less WIP) performs better. In all tested systems, the single-loop system was statistically significant better than a double-loop system.

However, statistically significant does not necessarily mean practically significant! The single-loop system would come at a cost of potentially quite uneven material distribution as shown in Fig. 4 part a) above. Besides reduction in WIP, however, lean manufacturing also emphasizes a level production. The idea of having a pile of material at one point but none at the other goes against lean thinking. It is difficult to quantify, but it is definitely one reason against using a single-loop system despite lower WIP.

For a delivery performance of around 95%, the single-loop system required about 20% less WIP in both cases. Hence, there would be a small benefit in WIP. Yet, these results were achieved only after exhaustive testing of all possible combinations of number of kanban and FIFO capacities. In reality, such an exhaustive test is usually not possible. Instead, the number of kanban cards are estimated using either gut feeling or a kanban formula -which by itself is also nothing but a rough estimation with a significant margin of error. For the FIFO capacity, an expert estimate is the most common way in industry, which is also quite uncertain. Overall, it is unlikely that a real line will get the "just right" number of kanban cards and FIFO capacity to benefit from these optimal conditions. As a conclusion, using a single-loop has a small advantage in respect to WIP and delivery performance. However, in practice there are many other considerations that can easily overrule the small WIP benefit of a single-loop system.

Fig. 1 .

 1 Fig. 1. Two processes connected through FIFO within one kanban loop (a) or split into two different kanban loops using a supermarket (b)

Fig. 2 .

 2 Fig. 2. Delivery performance vs. WIP for system 1 with equal cycle times

Fig. 3 .

 3 Fig. 3. Delivery performance vs. WIP for system 2 with unequal cycle time, P2 faster

Fig. 4 .

 4 Fig. 4. WIP locations during low demand

Table 1 .

 1 Overview of the mean time between parts of the simulated systems. All times were exponentially distributed

	System	Cycle Time Cycle Time Customer P1 P2 Takt
	1	10	10	12
	2	10	9	12


Damiano Nunzio Arena
email: damiano.arena@epfl.ch

Dimitris Kiritsis
email: dimitris.kiritsis@epfl.ch

A Method Towards Modelling and Analysis of Semantically-enriched Reconfigurable Manufacturing Systems

Keywords: Reconfigurable manufacturing systems, Colored petri net, Ontologies

Modelling and simulation are two relevant facets for thorough and effective analysis of industrial systems that nowadays have to cope with the evergrowing complexity of the industrial processes and the need of modelling flexibility and knowledge sharing. For all these reasons, the following work seeks to explore and combine together different methodologies by exploiting their best features. In particular, the current research aims to combine semantic technologies, such as ontologies, and high-level Petri nets to revamp the actual assembly systems. Thus, key research concepts are presented, explaining such potential integration and providing a short example of the dynamic configuration of an assembly system within a semantically enriched modelling environment.

Problem Statement

In today's manufacturing industry, staying in business is a life-and-death issue for many manufacturing companies. It is well-known that the one thing most surviving or winning manufacturing companies have in common is continuous improvement and adaptation of their manufacturing systems. During the last few decades, these have thoroughly evolved, from low volume, high variety jobshop production systems to more robust mid-volume and variety flexible manufacturing systems. Nonetheless, manufacturing systems still suffered from low responsiveness and large capital investment until the introduction of reconfigurable manufacturing systems. Reconfigurability can be defined as the ability to repeatedly change capacity and functionality in a cost-efficient way, in order to meet different demand situations in terms of variation in volume as well as in product characteristics [START_REF] Mehrabi | Reconfigurable Manufacturing Systems: Key to Future Manufacturing[END_REF]. This ability can be achieved at different enterprise levels, e.g. network, factory, segment, system, cell, workstation [START_REF] Wiendahl | Changeable Manufacturing -Classification, Design and Operation[END_REF].

Though there is a substantial amount of research work available in the domain of reconfigurable systems, especially at system level [START_REF] Andersen | Reconfigurable Manufacturing on Multiple Levels: Literature Review and Research Directions[END_REF], systems with full level of reconfigurability are still non-existent [START_REF] Elmaraghy | Flexible and Reconfigurable Manufacturing Systems Paradigms[END_REF]. In particular, in the domain of developing Reconfigurable Manufacturing Systems (RMS), just limited research that incorporates its true dynamic, rapid nature and accurate decision making in complex systems is available.

Towards development of Reconfigurable Manufacturing Systems, several promising models have been proposed in the past two decades [START_REF] Rakesh | A Framework for Simultaneous Recognition of Part Families and Operation Groups for Driving a Reconfigurable Manufacturing System[END_REF][START_REF] Nourelfath | Availability Modeling and Optimization of Reconfigurable Manufacturing systems[END_REF][START_REF] Da Silva | Modeling of Reconfigurable Distributed Manufacturing Control Systems[END_REF][START_REF] Lohse | Towards WebEnabled Design of Modular Assembly Systems[END_REF]. However, these models are only limited to control, physical and structural aspects that would support reconfiguration but lacked a rapid reconfigurability and decision making capabilities.

To summarize, our effort in this work focuses on the definition of a semanticenriched modelling environment for Reconfigurable Manufacturing Systems taking full advantage of the dynamic properties of ontologies and Petri nets.

Proposed Approach

The objective of this research is to investigate and support the re-configurability of manufacturing systems by applying CPN modelling language and Knowledge Engineering (KE) methodologies, such as Ontologies. The rationale of this work is two-fold:

-Semantic extraction and modelling of Reconfigurable Manufacturing Systems. -Integration of the aforementioned enabling technologies to support the dynamic design of Reconfigurable Manufacturing Systems.

The key feature of this approach resides with the integration of Semantic Techniques and Colored Petri Nets. This potential integration seeks to bridge the lack of interoperability between such methodologies by creating a Semantically Enriched Environment where a RMS can be (dynamically) instantiated.

CPNs are proven to be suitable for modelling the system structure and behavior, therefore, RMS concepts are mapped into CPN ones, and then transformed into CPN-oriented elements. The resulting CPN model can be, therefore, verified and simulated in order to explore and perform either quantitative or qualitative analysis of the system [START_REF] Tysz | Modeling a Flexible Manufacturing Cell Using Stochastic Petri Nets With Fuzzy Parameters[END_REF]. In particular, qualitative analysis searches for structural properties [START_REF] Kahraman | Manufacturing System Modeling Using Petri Nets[END_REF], such as:

absence of deadlocks absence of overflows presence of certain mutual exclusions (in case of resource sharing) Quantitative analysis, instead, looks for performance properties such as:

throughput, average completion times average queue lengths utilization rates

The simulation outcomes can be, hence, reasoned in order to feedback the system and achieve continuous re-adaptation and improvement. Figure 1 shows the proposed (closed-loop) architecture together with an overview of the main system elements: -Data Silos, manufacturing/assembly data that are a vital element for the RMS itself, which are either structured or unstructured; -DS, decision system based on semantic technologies, that aims to provide data integration and reasoning features; -Semantic Ecosystem, where domain-specific ontology elements are related to one another to enable CPN concepts inferring from RAS ones; -CPN engine to perform the above-mentioned assessments.

A Reconfigurable Manufacturing System poses itself a modelling challenge because of its dynamic nature. On the other hand, Petri Net formalism, and in particular CPN, has a general-purpose nature and it is based on strong math foundations, which results very suitable for both modelling and analysis phases of reconfigurable systems.

Method Conceptualization

The backbone of this solution is represented by the semantic-enriched environment through which all the domain specific concepts are outlined and related each other. Particular emphasis has to be given to the non-trivial semantics of the selected modelling language (CPN), which extends the simple PN formalism by introducing some enriched features. In fact, the so-called CPN Ontology (see Figure 2) should consists of basic PN concepts (place, transition, arc, and token) plus high-level ones (see table 1).

The RMS Ontology, should consists, instead, of domain specific concepts, such as Equipment, Components, Worker roles, Work Station (see Figure 3). However, some details about this ontology models have been omitted. As mentioned earlier, ontologies themselves do not provide simulable models. The introduction of PN-based concepts, hence, aims to bridge this lack of simulation through the translation of RMS elements into CPN ones. In this regards, Zhou et.al [18] suggest an interpretation of the simple PN elments such as Places, Transitions and directed Arcs (see Table 2), which can be, therefore, inferred through the semantic models. The proposed approach, in fact, aims to set inference rules to automatically perform the aforementioned concepts mapping and, then, provide a PN-based semantic-enriched description of the re-configurable assembly system. For example, using a human readable syntax, we can set the following rule:

hasMachine (? Activity , ? Machine ) ∧ hasMachineStatus (? Machine , ? MachineStatus ) ⇒ connectsPlaceTo (? PTArc , ? Transition ) ∧ hasPTArc (? Place , ? PTArc ) This is valid according to the assumption that an Activity is intepreted as a Transition and a MachineStatus as a Place. These can be then instantiated as shown in Figure 4. -The sequence can be optimized (respecting the technological specifications) -The work load of the assigned operator should be modified by splitting the execution of those steps among more operator, e.g. increasing the efficiency of the process. -The expected output should be adapted to respond new customer requirements Thus, starting from the initial configuration, the system will require some adjustments and consequence re-assessment. For instance, a small portion of the model will be reconfigured (see Figure 6) according to the new requirements revealed by the DS. In fact, once the system receives an input from the DS regarding the need of reconfiguring the system, the new Manufacturing System can be instantiated within the semantic framework, then, translated into Petri

Conclusions

In the current research we focus on the conceptualization of a modelling framework for Reconfigurable Manufacturing Systems based on Colored Petri Nets and Knowledge Engineering technologies, such as Ontologies. The scope of the presented work is to provide an overview of the key concepts, modelling issues and potential solutions together with a short example of a reconfigurable assembly system. Petri nets are used to model the Manufacturing System while ontologies are exploited to achieve system interoperability, integration and reusability through semantics. However, the work is still at an early stage and requires some effort in terms of both analysis and implementation in order to explore more critical design facets and pinpoint eventual drawbacks, which might prevent the full interoperability among the system elements. In particular, future work will necessitate the formal assessment of design and deployment requirements (e.g. semantics integration, verification and simulation metrics), the selection of a suitable development environment, and the instantiation of a real case scenario. In this regard, the presented modelling approach has been applied to RMS example but it will be re-used and further tested in the context of Satis-Factory European research project in order to support the analysis and design of dynamically evolving shop floor operations.

Fig. 1 .

 1 Fig. 1. System Architecture

Fig. 2 .Fig. 3 .

 23 Fig. 2. CPN Ontology

Fig. 4 .

 4 Fig. 4. PlacePTArcTransition inference-based instantiation

  5). The system might be influenced by different conditions, for example:

Fig. 5 .

 5 Fig. 5. RMS initial configuration

Fig. 6 .

 6 Fig. 6. Reconfigured Manufacturing System

Table 1 .

 1 CPN ontology classes and relations

			Class Property
	Class	subClassOf	Name	Range
	CPN Element Thing	-	-
	Place	CPN Element hasTokens	Token
	Transition	CPN Element hasTInscription	Inscription
	Arc	CPN Element hasAInscription	Inscription
	PTArc	Arc	connectsTransitionTo	Transition
	TPArc	Arc	connectsPlaceTo	Place
	Token	CPN Element hasInfo	TokenInfo
	TokenInfo	Token	-	-
	Inscription	CPN Element -	-
	A Inscription Inscription	definesFlowRuleOn	Arc
	T Inscription Inscription	definesExecutionRuleOn Transition

Table 2 .

 2 Interpretation of the PN elements

	PN Elements Interpretation
	Places	Resource status, operations and conditions
	Transitions	Operations, processes, activities and events
	Directed Arcs	Material, resource, information, and control flow direction