Siavash Javadi
email: siavash.javadi@mdh.se

Mads Bejlegaard

Ann-Louise Andersen

Jessica Bruch
email: jessica.bruch@mdh.se

The Introduction Process of Low-Volume Products: Challenges and Potentials of Information Management

Keywords: Design-manufacturing interface, Product development, Productiondesign integration

The product introduction process plays an important role in development of new products and launching them to the market on-time with a high quality. The product introduction process has been studied primarily in high-volume manufacturing industries and therefore, the influences of the characteristics of low-volume manufacturing industries on the product introduction process has not been investigated. The aim of this paper is to study challenges and potentials of information management during the product introduction process in low-volume manufacturing industries by a multiple-case study in two Scandinavian low-volume manufacturing companies. The paper contributes in covering the knowledge gap about the information management during the product introduction process in low-volume manufacturing industries.

Introduction

Manufacturing companies are forced to develop and launch new products to the market more frequently with a high quality because of different factors such as in-creased competition in the globalized market, introduction of new technologies and faster obsolescence of the products. The product introduction process as the final sub-process of the product development is of high importance to reduce the production disturbances during the early stages of the production of new products and to reach the intended quality, production goals and time to market/payback [START_REF] Johansen | Collaborative Product Introduction within Extended Enterprises[END_REF][START_REF] Ruffles | Improving the New Product Introduction Process in Manufacturing Companies[END_REF]. An effective management of information in the product introduction process is central for the success of the product introduction process [START_REF] Frishammar | Managing Information in New Product Development: A Conceptual Review, Research Propositions and Tentative Model[END_REF][START_REF] Adler | Interdepartmental Interdependence and Coordination: The Case of the Design/Manufacturing Interface[END_REF][START_REF] Bruch | Characteristics Affecting Management of Design Information in the Production System Design Process[END_REF][START_REF] Fjällström | Information Enabling Production Ramp-Up[END_REF].

Although information management in the product introduction process has been studied in the context of product development [START_REF] Frishammar | Managing Information in New Product Development: A Conceptual Review, Research Propositions and Tentative Model[END_REF][START_REF] Frishammar | Managing Information in New Product Development: A Literature Review[END_REF], production system development [START_REF] Bruch | Characteristics Affecting Management of Design Information in the Production System Design Process[END_REF] and production ramp-up [START_REF] Fjällström | Information Enabling Production Ramp-Up[END_REF], the influences of the characteristics of low-volume manufacturing industries on it has remained unexplored. Therefore, the aim of this paper is to study challenges and potentials of information management during the product introduction process in low-volume manufacturing industries. To achieve this aim, a multiple-case study has been conducted in two Scandinavian low-volume manufacturing companies.

Frame of reference

The product introduction process is the finishing process of product development projects which is also known as the industrialization process [START_REF] Bellgran | Production Development: Design and Operation of Production Systems[END_REF][START_REF] Berglund | Challenges in a Product Introduction in a Cross-Cultural Work System -A Case Study Involving a Swedish and a Chinese Company[END_REF]. The product introduction process influences critical outcomes of the product development projects such as time to market and product quality [START_REF] Adler | Interdepartmental Interdependence and Coordination: The Case of the Design/Manufacturing Interface[END_REF]. Bellgran and Säfsten [START_REF] Bellgran | Production Development: Design and Operation of Production Systems[END_REF] define the product introduction process as "transferring from engineering design to production including those activities required to make the product manufacturable and to pre-pare production". Fewer disturbances during production, a shorter time to market and higher quality of the products are some outcomes of a well-implemented product introduction process [START_REF] Fjällström | Information Enabling Production Ramp-Up[END_REF][START_REF] Almgren | Towards a Framework for Analyzing Efficiency During Start-Up: An Empirical Investigation of a Swedish Auto Manufacturer[END_REF]. The product introduction process goals are to develop a production system for production of a product [START_REF] Johansen | Collaborative Product Introduction within Extended Enterprises[END_REF][START_REF] Bellgran | Production Development: Design and Operation of Production Systems[END_REF] and to adapt product and production system together to ensure the manufacturability of the product [START_REF] Johansen | Collaborative Product Introduction within Extended Enterprises[END_REF][START_REF] Ruffles | Improving the New Product Introduction Process in Manufacturing Companies[END_REF]. Frishammar [START_REF] Frishammar | Managing Information in New Product Development: A Conceptual Review, Research Propositions and Tentative Model[END_REF] summarizes the activities of the product introduction process as the mid-phase of new product development process. These activities include development of product and production system, test and refinement of the product functionality mainly by development of engineering prototypes, test and refinement of the production system and adapting the product and production system together by production of pre-series and reaching the production goals and training the production personnel during the production ramp-up [START_REF] Johansen | Collaborative Product Introduction within Extended Enterprises[END_REF][START_REF] Frishammar | Managing Information in New Product Development: A Conceptual Review, Research Propositions and Tentative Model[END_REF][START_REF] Fjällström | Information Enabling Production Ramp-Up[END_REF][START_REF] Javadi | Characteristics of Product Introduction Process in Low-Volume Manufacturing Industries: A Case Study[END_REF]. However, the phases of product introduction process in low-volume manufacturing industries are restricted to development of product and production system, testing and refinement of the functionality of the product and limited production of pre-series and no conventional ramp-up phase is feasible [START_REF] Javadi | Characteristics of Product Introduction Process in Low-Volume Manufacturing Industries: A Case Study[END_REF][START_REF] Andersen | Investigating the Impact of Product Volume and Variety on Production Ramp-up[END_REF]. This is primarily because of high costs, low production volume, and high variety of the products in low-volume manufacturing companies [START_REF] Javadi | Characteristics of Product Introduction Process in Low-Volume Manufacturing Industries: A Case Study[END_REF][START_REF] Andersen | Investigating the Impact of Product Volume and Variety on Production Ramp-up[END_REF] which lead to following a full make-to-order production policy [START_REF] Jina | Applying Lean Principles for High Product Variety and Low Volumes: Some Issues and Propositions[END_REF].

However, the novelty of products and production systems in low-volume manufacturing industries are usually low [START_REF] Javadi | Characteristics of Product Introduction Process in Low-Volume Manufacturing Industries: A Case Study[END_REF] which can facilitate the product introduction process based on Almgren's [START_REF] Almgren | Pilot Production and Manufacturing Start-up in the Automotive Industry[END_REF] model of complexity of product introduction process. The products in low-volume manufacturing industries are usually modified versions of the existing products [START_REF] Javadi | Characteristics of Product Introduction Process in Low-Volume Manufacturing Industries: A Case Study[END_REF]. In addition, the production systems of low-volume manufacturing companies are usually flexible enough to produce several products and their variants and to accommodate new products to avoid high costs of developing dedicated production systems for each product [START_REF] Javadi | Characteristics of Product Introduction Process in Low-Volume Manufacturing Industries: A Case Study[END_REF][START_REF] Andersen | Investigating the Impact of Product Volume and Variety on Production Ramp-up[END_REF].

One of the main sources of disturbances during the product introduction process is lack of integration between design and production [START_REF] Almgren | Pilot Production and Manufacturing Start-up in the Automotive Industry[END_REF][START_REF] Surbier | A Comparative Study on Production Ramp-up: State-ofthe-Art and New Challenges[END_REF]. The production-design integration can be achieved by 1. More formal and structured activities between the departments such as processes, routines and planned meetings and flow of documents 2. Informal unstructured continuous relationships between departments which lead to developing common understanding, sharing resources and achieving shared objectives [START_REF] Berglund | Challenges in a Product Introduction in a Cross-Cultural Work System -A Case Study Involving a Swedish and a Chinese Company[END_REF]. Information management i.e. acquisition, sharing and using the information [START_REF] Bruch | Characteristics Affecting Management of Design Information in the Production System Design Process[END_REF][START_REF] Frishammar | Managing Information in New Product Development: A Literature Review[END_REF] plays an essential role in supporting the design-production integration and avoiding or mitigating disturbances during the product introduction process [START_REF] Fjällström | Information Enabling Production Ramp-Up[END_REF][START_REF] Frishammar | Managing Information in New Product Development: A Literature Review[END_REF] e.g. by reducing uncertainty and equivocality [START_REF] Frishammar | Beyond Managing Uncertainty: Insights from Studying Equivocality in the Fuzzy Front End of Product and Process Innovation Projects[END_REF]. Therefore, this paper aims at investigating challenges and potentials of information management during the product introduction process in low-volume manufacturing industries, which has not been considered in the literature [START_REF] Surbier | A Comparative Study on Production Ramp-up: State-ofthe-Art and New Challenges[END_REF].

Research method

Case study is a suitable method for in-depth study of a contemporary phenomenon when the knowledge is limited about the phenomenon [START_REF] Meredith | Building Operations Management Theory Through Case and Field Research[END_REF] which was the case for the subject of this study. Two product development projects were selected as cases from two Scandinavian companies based on possession of the characteristics of low-volume manufacturing companies mentioned by Jina et al. [START_REF] Jina | Applying Lean Principles for High Product Variety and Low Volumes: Some Issues and Propositions[END_REF]. The first case study, hereafter called Case A, was conducted from October 2012 to September 2013 in a company which develops and produces underground construction and mining equipment. The company is a large company with over 1300 employees. The products of the company were produced in five product families including several variants with numerous options to meet the requirements of different customers and markets. The production activities at the company included the final assembly of the products and sub-assembly of some of the product modules.

The second case, here referred to as Case B, was conducted in a company producing earth-moving equipment. The product series contain three main types of machines with a total of 30 variants, which can be further configured through an additional eight parameters with numerous different options to choose from. The vast majority of the products are customized from well-defined modular product architectures. The case study was conducted from august 2014 to June 2015. The company has approximately 150 employees and therefore, is considered as a small-medium enterprise. All of the products offered by the company are developed and produced in the same location, where production activities cover the manual final assembly, and a steel processing setup that includes manual handling of large components and automatic welding.

In both cases, different sources of data were used including the observation of project meetings and events, documents related to the disturbances during the product introduction process and interviews. Eight and three semi-structured interviews were conducted with the product development project team members of Case A and Case B, respectively. In addition, some follow up interviews were conducted with the production operators to validate and complete the findings of the case studies during 2015. The collected data from these interviews were primarily covered. Five and two final assembly operators were interviewed in Company A and Company B, respectively about information on new products received by assembly operators and production equipment for new product introduction. Initially, the gathered data from each case were recorded and analysed separately to understand how information management during the product introduction in low-volume manufacturing industries is influenced by the characteristics of such industries. Thereafter, a cross-case comparison was conducted to compare the similarities and differences of the cases.

4

Empirical findings

Case A

The goal of the product development project was a general modification of one of the existing products. The product was planned to be produced in the existing production system. The assembly line was designed to produce different products with slight changes. Such flexibility was achieved mainly by manual operations, general-purpose tools and material handling equipment. The product development project was managed according to a stage-gate model and the project team consisted of different functions such as product design, production, product introduction, purchasing, marketing and product support. The product introduction manager responsibility was basically facilitating the product introduction process by coordinating activities between design and production and considering the limitations and requirements of the production system for the production of the new product. This coordination was necessary because of inter-departmental barriers between design and production as well as their separate locations. Some of the main activities followed by the product introduction manager were collecting the requirements of the production and sharing them with the project team during the development phase, coordinating design reviews to update production personnel about new features of the products and the manufacturability implications of those features and developing assembly sequences and instructions during development of the prototypes.

After the product design phase, two prototypes were developed outside of the normal production facilities with very limited contribution of production personnel because of limited human resources and prioritizing involvement of production personnel in the ongoing production over the product development projects. The assembly sequences and instructions were developed during this phase. In addition to the proto-types, four first products were planned as pre-series to be produced in the production system. However, because of low and discontinuous demand for the product, only two of those preseries were produced immediately after the prototypes. Production of the pre-series encountered many disturbances. These disturbances, their causes and solutions were registered in a database. The most frequent and considerable types of these disturbances were lack of information about the product details, lack of considering manufacturability of the products and late consideration of required changes and limitations of the production system. In addition, based on the follow-up interviews, the information received by production about the new products was incomplete, incorrect and/or ambiguous in many cases.

4.2

Case B

The product development project in Case B aimed at developing a completely new generation of a product. The product was planned to be produced in the existing production system with some necessary changes. The production system possessed the same characteristics as in Case A regarding its flexibility to produce different products and their variants.

Because of the small size of the company, the product development project was managed in a less formalized way and with more face-to-face communications which were facilitated by co-location of different functions. The product design phase was conducted with limited involvement from other functions than product development. However, the designers' knowledge about the production system was extensive because of their long experience at the company and continuous informal communication with the production. After the development phase, two prototypes were developed to test and refine the functionality of the product. No pre-series were produced. Instead, mutual adjustments by informal face-to-face communication between design and production and other functions continued after the start of the production to remove the remaining problems and adjust product and production system together.

Among the predominant disturbances during production start-up were difficulties in implementing and specifying an externally-supplied main component. In addition, necessary changes in the production system were implemented late because of limited resources for designing and implementing new tooling, and due to prioritising quick market introduction over an optimal production setup. The follow-up interviews justified that the information about parts were often in-complete or incorrect during production start-up. The respondents also mentioned that a direct communication with few intermediaries between design and production was a great advantage in handling the product introduction. The advantage of this was that the experience of the operators were used directly in development, which in addition increased the awareness of the operators and their perceived project responsibility.

Discussion

Managing information during the product introduction process was influenced by the characteristics of the studied low-volume manufacturing companies in different ways. Limited resources in both cases led to challenges regarding the production-design integration. In both cases, the early involvement of production in the product introduction process was limited because the production personnel had to prioritise the ongoing production activities over the product development projects. However, some processes such as collecting the requirements of production at the start of development phase, using the design reviews to inform production about the new features of the product and production of four pre-series product were foreseen in Case A. In Case B the integration was supported more by co-location of design and production and informal relations whereas these informal communications were limited in Case A because of interdepartmental barriers and separate locations of design and production.

The limited integration between design and production resulted also in difficulty of acquiring information from production personnel about the required changes in the production systems and the requirements and limitation of the production system. Furthermore, sharing the information about the new features of the product and their implications for production with the production personnel was challenging because of lack of integration which is in line with the propositions of Frishammar and Ylinenpää [START_REF] Frishammar | Managing Information in New Product Development: A Conceptual Review, Research Propositions and Tentative Model[END_REF]. High number of problems caused by neglecting design for assembly guidelines and requirements and limitations of the production systems in Case A and late delivery and installation of the new production equipment in both cases indicate that the information about the requirements and limitations of the production system are not managed properly during the product introduction project in the low-volume manufacturing industries [START_REF] Fjällström | Information Enabling Production Ramp-Up[END_REF][START_REF] Surbier | A Comparative Study on Production Ramp-up: State-ofthe-Art and New Challenges[END_REF]. This problem was intensified by extra focus of the designers as well as other project team members on the functionality of the products and under-prioritizing the manufacturability of the products because of the high customizability level and variety of the products. Especially in Case A, since the product was a modified version of an existing product, in many instances the effects of the modifications on the other parts and components were not considered and the information about them was not acquired and shared with production.

In addition, because of lack of integration, no formal process was planned for sharing and using the acquired information about the problems and disturbances. In Case A, a database was used for registering the information about product-related problems and their solutions. However, there was no foreseen mechanism for sharing the information with designers and using it in future products. In Case B, the information about problems and disturbances was not documented nor shared. Furthermore, the follow-up interviews showed that the lack of integration affects the characteristics of the information received by production about the new products. In both cases the information was not comprehensive, correct or/and clear in several instances. Incorrect/incomplete information about small connecting parts and incorrect/incomplete assembly instructions are some examples of such problems. There-fore, in many instances using the received information was impossible or difficult.

Beside the lack of integration, limited opportunities for test and refinement of the products and production system caused challenges for acquiring and sharing the information about the disturbances and critical events. Since there were limited opportunities for test and refinement, many of the problems and critical events surfaced late in the project, i.e. after the start of production. Therefore, acquisition of the in-formation about them and eliminating them was not possible during the earlier phases. This lack of information about the disturbances and non-conformities increased the level of information uncertainty [START_REF] Frishammar | Beyond Managing Uncertainty: Insights from Studying Equivocality in the Fuzzy Front End of Product and Process Innovation Projects[END_REF]. Another factor which affected the information management in the studied product introduction processes was introducing new products in the current production systems with slight modifications. Since the production system was considered primarily "as is" by the product development team, information on the required changes related to the production system development were acquired and shared late. Late consideration of the required changes in production system in Case A and late implementation of them in both cases was partially caused by this characteristic. However, this reduced novelty of production systems in product introduction process in low-volume manufacturing companies can potentially lead to reduced complexity of information management. The low newness level of the production system can provide the de-signers and production personnel with information about the introduction of previous products in that production system and help them to avoid similar disturbances during the introduction of new products. The complexity could be reduced even more when the product is a modified version of an existing product like Case A. However, a process should be established to acquire information from the introduction of new products, to share the information with the product development team members including the designers and production personnel and to use it during the introduction of the future products. Table 1 summarizes the discussed challenges and potentials of information management during the product introduction process in low-volume manufacturing companies.

Table 1. The challenges and potentials of information management caused by the characteristics of product introduction process in low-volume manufacturing industries

Characteristics of the product introduction process in low-volume companies

Information management

Challenges Potentials

Lack of resources -Reduced integration between design and production -Difficulty of acquiring necessary information from production -Difficulty of sharing information about the new products with production -Facilitating acquiring and sharing the information by encouraging face-to-face and informal relations by co-location of design and production Lack of opportunities for test and refinement of products and production systems -Fewer opportunities for acquiring information about problems and disturbances -Increased information uncertainties about the products _ Using the similar production system for production of new products -Late acquisition and sharing of information about required changes in production -Sharing and using information from introduction of previous products to reduce the complexity Modifying existing products instead of developing completely new products -Uncertainties about the affected parts and components and the required information -Sharing and using information from introduction of previous products to reduce the complexity

Conclusions

Regarding its aim, this paper achieved to identify a number of challenges and potentials of information management during the product introduction process in low-volume manufacturing industries. The characteristics of product introduction in low-volume manufacturing industries impose difficulties of timely and complete acquisition and sharing of information between production and design. However, those characteristics provide a potential to facilitate the product introduction process by reusing the information from introduction of previous similar products. In this regard, the paper contributes to covering the knowledge gap about the information management during the product introduction process in low-volume manufacturing industries. The paper also provides practitioners with insights about management of information during the product introduction process.

The paper provides the basis for future research about the further details of information management during the product introduction process in low-volume manufacturing companies and how to use the information management to facilitate and support the product introduction process in such industries.


Veronica Lindström
email: veronica.lindstrom@liu.se

Niklas Ingesson
email: niklas.ingesson@titanx.com

Mapping a Value Stream with the Perspective of Sustainability

Keywords: Lean production, Manufacturing, Production operations, Value stream mapping

Companies align lean production and sustainability differently depending on organization model. Lean provides social foundation for sustainability and makes it possible to implement sustainability, and integrate lean and sustainability. The work presented here maps a current value stream with measures from different methodologies presented in the literature. The objective of this paper is to integrate sustainability measures with a traditional value stream mapping. Economic, environmental, and societal metrics are presented. The result indicates that the interest of the different metrics depends on the role within the organization..

Introduction

Industrial companies that compete on a global market can choose to differentiate their manufacturing strategy depending on product family and its niche consumer. If industrial companies choose to differentiate their products towards a more narrow competitive scope and thus apply a differentiation strategy [START_REF] Porter | Competitive Advantage: Creating and Sustaining Superior Performance[END_REF], sustainability as a competitive priority may be an order winner for a niche market [START_REF] Jovane | The Incoming Global Technological and Industrial Revolution Towards Competitive Sustainable Manufacturing[END_REF] and may improve international competitiveness [START_REF] Epstein | Making Sustainability Work: Best Practices in Managing and Measuring Corporate Social, Environmental, and Economic Impacts[END_REF]. The competitive priority sustainability is thus adding a higher value to those niche markets and its customers. However, industrial companies within the car and truck industry compete today with products that are mature and thus need to find ways to add value besides continuous total cost reductions. Companies within the car and truck industry have applied Lean production for some decades with the purpose to eliminate waste in their value streams to add value. One common used tool is Value Stream Mapping (VSM). VSM is a tool to find and eliminate waste in a value stream. The original value stream is defined as the value stream for the end customer, or consumer. Lean thinking provides a way to specify value [START_REF] Womack | Lean Thinking: Banish Waste and Create Wealth in Your Corporation[END_REF]. The basis for lean production development is to eliminate waste. According to the theory of lean thinking, one can learn to see the waste by mapping a value stream [START_REF] Rother | Learning to See: Value Stream Mapping to Add Value and Eliminate Muda[END_REF]. Recent research on the application of value stream mapping adds sustainability measures and integrates thus additional measures to evaluate environmental impact and societal well-being [START_REF] Brown | Sustainable Value Stream Mapping (Sus-VSM) in Different Manufacturing System Configurations: Application Case Studies[END_REF][START_REF] Faulkner | Sustainable Value Stream Mapping (Sus-VSM): Methodology to Visualize and Assess Manufacturing Sustainability Performance[END_REF].

The work presented in this paper focuses on the integration of sustainability measures in a traditional VSM. Environmental measurements have been applied similar to the work of Sus-VSM [START_REF] Brown | Sustainable Value Stream Mapping (Sus-VSM) in Different Manufacturing System Configurations: Application Case Studies[END_REF][START_REF] Faulkner | Sustainable Value Stream Mapping (Sus-VSM): Methodology to Visualize and Assess Manufacturing Sustainability Performance[END_REF]. The ergonomic measurements have been applied according to the study presented as the method ErgoVSM [START_REF] Jarebrant | ErgoVSM: A Tool for Integrating Value Stream Mapping and Ergonomics in Manufacturing[END_REF].

Frame of Reference

Sustainability in Production Operations

Sustainability at the company level concerns the development of products, processes, and business models [START_REF] Jovane | The Incoming Global Technological and Industrial Revolution Towards Competitive Sustainable Manufacturing[END_REF]. Therefore, product and process innovations will be needed to achieve sustainable production [START_REF] Jayal | Sustainable Manufacturing: Modeling and Optimization Challenges at the Product, Process and System Levels[END_REF]. It also requires a holistic view and improved product performance models and optimization of individual manufacturing processes, to give some examples [START_REF] Jayal | Sustainable Manufacturing: Modeling and Optimization Challenges at the Product, Process and System Levels[END_REF]. Several articles in the literature describe sustainable production. Issues within this area include managing processes with an input such as energy, people, equipment and machines with the objective of reducing waste, carbon footprint, rework, inventory and delays [START_REF] Gunasekaran | Sustainability of Manufacturing and Services: Investigations for Research and Applications[END_REF]. Sustainable production operations should lead to improvements in competitive priorities such as flexibility, customization, responsiveness, dependability, cost reduction and high quality of products and services [START_REF] Gunasekaran | Sustainability of Manufacturing and Services: Investigations for Research and Applications[END_REF]. To promote sustainability-driven decision-making, a socalled value creating framework could be applied in organizations where five factors are considered; product, process, equipment, organization, and human [START_REF] Bilge | Model-based Approach for Assessing Value Creation to Enhance Sustainability in Manufacturing[END_REF].

Companies applying lean manufacturing and its concepts align sustainability differently in their respective organizations depending on organizational model in the company [START_REF] Longoni | Cross-functional Executive Involvement and Worker Involvement in Lean Manufacturing and Sustainability Alignment[END_REF]. Companies with a traditional organizational model tend to lack executive involvement and worker commitment that leads to that sustainability is underdevel-oped. On the other extreme, companies with advanced organizational model tend to involve workers, and those companies have also a high cross-functional executive involvement [START_REF] Longoni | Cross-functional Executive Involvement and Worker Involvement in Lean Manufacturing and Sustainability Alignment[END_REF]. To achieve sustainability in production operations, managers are suggested to apply methods and programs like just-in-time production, lean, total quality management, Kanban etc. [START_REF] Gunasekaran | Sustainability of Manufacturing and Services: Investigations for Research and Applications[END_REF]. According to Piercy and Rich [START_REF] Piercy | The Relationship Between Lean Operations and Sustainable Operations[END_REF], lean provides social foundation for sustainability and pairs it with technical system, which makes it possible to implement sustainability and thus integrate lean and sustainability [START_REF] Piercy | The Relationship Between Lean Operations and Sustainable Operations[END_REF].

Sustainability and Value Streams

Lean production principles start with defining "value" [START_REF] Womack | Lean Thinking: Banish Waste and Create Wealth in Your Corporation[END_REF]. A value stream is the "set of all the specific actions required to bring a specific product through the three critical management tasks of any business: the problem-solving task running from concept through detailed design and engineering to production launch, the information management task running from order-taking through detailed scheduling to delivery, and the physical transformation task proceeding from raw materials to a finished product in the hands of the customer." (Womack and Jones, page 19) [START_REF] Womack | Lean Thinking: Banish Waste and Create Wealth in Your Corporation[END_REF].

Sustainability is defined as taking into consideration the triple bottom line, i.e. economic, environmental, and societal goals [START_REF] Jovane | The Incoming Global Technological and Industrial Revolution Towards Competitive Sustainable Manufacturing[END_REF][START_REF] Elkington | Cannibals with Forks: The Triple Bottom Line of 21st Century Business[END_REF].

Different Types and Metrics of Sustainable Value Stream Mappings

Applying Lean production means to get the knowledge, leadership and it starts to identify the value streams [START_REF] Womack | Lean Thinking: Banish Waste and Create Wealth in Your Corporation[END_REF]. Once you have identified a value stream, one can start to map it. Value Stream Mapping, VSM, is a lean tool that aims to reduce waste [START_REF] Womack | Lean Thinking: Banish Waste and Create Wealth in Your Corporation[END_REF]. VSM can be a communication tool or a business planning tool, and a tool for managing the change processes of the company [START_REF] Rother | Learning to See: Value Stream Mapping to Add Value and Eliminate Muda[END_REF]. The mapping begins at "a door-to-door level" and includes the mapping of material-and information flows of operations. The measurements of the original VSM are mainly time and inventory (quantity) [START_REF] Rother | Learning to See: Value Stream Mapping to Add Value and Eliminate Muda[END_REF]. Sustainable value stream mapping (Sus-VSM) is a VSM that, in addition to lead time, includes environmental and societal metrics [START_REF] Brown | Sustainable Value Stream Mapping (Sus-VSM) in Different Manufacturing System Configurations: Application Case Studies[END_REF][START_REF] Faulkner | Sustainable Value Stream Mapping (Sus-VSM): Methodology to Visualize and Assess Manufacturing Sustainability Performance[END_REF]. The metrics types are thus economic, environmental, and societal metrics [START_REF] Faulkner | Sustainable Value Stream Mapping (Sus-VSM): Methodology to Visualize and Assess Manufacturing Sustainability Performance[END_REF]. The environmental metrics consist of energy consumption, raw material usage, and process water usage. The societal metrics consist of the metrics of physical load and work environment metrics such as noise, risks for electrical systems, hazardous chemical/materials used, pressurized systems, and high-speed components [START_REF] Brown | Sustainable Value Stream Mapping (Sus-VSM) in Different Manufacturing System Configurations: Application Case Studies[END_REF].

Product Sustainability Index (ProdSI) is an assessment of the overall product sustainability throughout its product life cycle [START_REF] Shuaib | Product Sustainability Index (ProdSI): A Metrics-based Framework to Evaluate the Total Life Cycle Sustainability of Manufactured Products[END_REF]. ProdSI is the overall aggregated product sustainability performance index, which consists of three subindex; economic, environmental, and societal. The ProdSI methodology suggests that individual metrics should be used and customized for each specific case [START_REF] Shuaib | Product Sustainability Index (ProdSI): A Metrics-based Framework to Evaluate the Total Life Cycle Sustainability of Manufactured Products[END_REF].

ErgoVSM is a lean tool for integration of ergonomics in manufacturing in a value stream mapping activity [START_REF] Jarebrant | ErgoVSM: A Tool for Integrating Value Stream Mapping and Ergonomics in Manufacturing[END_REF]. ErgoVSM considers physical exposure. It assesses physical exposure and is structured by tasks, value streams, and job level. Similar to Sus-VSM, ErgoVSM is embedded in the original VSM tool by Rother and Shook [START_REF] Rother | Learning to See: Value Stream Mapping to Add Value and Eliminate Muda[END_REF].

Methodology

The methodology used in this study is the case methodology. For the application of sustainability metrics in a value stream, a single case is used. The reason for choosing a single case was for the purpose of a pilot study [START_REF] Yin | Case Study Research: Design and Methods[END_REF]. The choice of the specific case was chosen for its location, accessibility, and its application of JIT and lean principles, which, according to theory, has relationship to sustainability [START_REF] Longoni | Cross-functional Executive Involvement and Worker Involvement in Lean Manufacturing and Sustainability Alignment[END_REF][START_REF] Piercy | The Relationship Between Lean Operations and Sustainable Operations[END_REF]. The advantage of a single case is that it can provide greater depth, and the limits of a single case is whether one can make any generalizations or conclusions [START_REF] Voss | Case Research in Operations Management[END_REF]. The study presented here was conducted from January through March 2016, and has included observations, interviews, and empirical data collection. To increase reliability and validity of this case, the principle informant in the case company was active during the whole process of setting up the research, data collection, and analyzing data. The approach presented here follows a typical deductive research, i.e. applying or revising an existing framework or hypothesis [START_REF] Barratt | Qualitative Case Studies in Operations Management: Trends, Research Outcomes, and Future Research Implications[END_REF]. Following suggested approach for deductive case studies, the unit of analysis should be articulated and the case justified [START_REF] Barratt | Qualitative Case Studies in Operations Management: Trends, Research Outcomes, and Future Research Implications[END_REF].

The Case Company and the Product of the Value Stream

TitanX is a dedicated supplier of engine and oil cooling products to the Commercial Vehicle industry. The company TitanX Engine Cooling AB in Linköping, Sweden, had a turnover of 329 Million SEK in year 2015. Their main customers are Volvo Trucks and Scania. The factory has been situated in Linköping since 1895. Since year 2008 the factory is owned by TitanX, which is a global manufacturer of powertrain cooling solutions to the commercial vehicle industry. The factory in Linköping, as well as the other manufacturing sites at TitanX, applies lean manufacturing principles. TitanX has their own production system called "TIPS" (TitanX Production System). The factory in Linköping strives towards operational excellence and World Class capabilities.

The product chosen for the application of the value stream mapping is a SFI cooler, see Figure 1. The production system of the SFI cooler has developed from a batch flow to a JIT production system, using Kanban and sequencing pull. The reason for choosing this product for mapping purposes is that this Fig. 1. Example of an SFI cooler cooler represents a modern manufacturing process and is thus interesting to map depending on possibility of future improvements. The product chosen consists of 9 turbulators of carbon steel, 18 plates of stainless steel plus on top plate, 8 foils of copper, two connections of stainless steel, and some rivets.

Data Collection

The data collection of this case study followed three different methodologies for the respective sustainability factor, see 3.2.1 to 3.2.3 below.

Economic Measures

The data collection of economic measures follows the VSM methodology by Rother and Shook [START_REF] Rother | Learning to See: Value Stream Mapping to Add Value and Eliminate Muda[END_REF]. First, a product family was chosen. A team of three people were mapping the value stream from "door-to-door" in the factory. Both material and information flows were mapped. Working times, cycle times, setup times, OEE, scrap rates, and inventory levels were collected by either clocking the times or capturing the data from machine data that is stored. Inventory levels were counted manually on the shop-floor. The lead time from door-to-door was calculated, as well as the value-added time.

Environmental Measures

The data collection of environmental measures follows the Sus-VSM methodology by Faulkner and Badurdeen [START_REF] Faulkner | Sustainable Value Stream Mapping (Sus-VSM): Methodology to Visualize and Assess Manufacturing Sustainability Performance[END_REF]. Process water consumption was measured per product and is captured as used water consumption, i.e. required and net water consumption was not captured. It is only one process that uses water; the brazing operation, see Figure 2. Raw material was captured via data of raw material in the business system AS/400. After the stamping operation, the product was weighted. In this way, the lost material by the stamping process could be measured. Additional components in the pre-assembly station 2 and assembly station were weighted. Energy consumption was measured as direct energy consumption per manufacturing process by using the power rating per machine and using cycle time per product. This data was retrieved from the MPS-system. Transportation power rates were not captured in this study as well as indirect energy usage such as lightning, heating and so on.

Societal Measures

The data collection of societal measures follows the ErgoVSM methodology by Jarebrant et al. [START_REF] Jarebrant | ErgoVSM: A Tool for Integrating Value Stream Mapping and Ergonomics in Manufacturing[END_REF]. Ratings for five ergonomics issues are considered in this methodology; postures, forces, physical variation, and porosity on the value stream level. A fifth ergonomic issue is the physical variation in the job of the operators in the value stream [START_REF] Jarebrant | ErgoVSM: A Tool for Integrating Value Stream Mapping and Ergonomics in Manufacturing[END_REF]. By rating task category per work station, the potential of variation of the job is rated. If there is a wide range of task categories per workstation, the potential is higher than if the tasks are monotonous [START_REF] Jarebrant | ErgoVSM: A Tool for Integrating Value Stream Mapping and Ergonomics in Manufacturing[END_REF]. The lower the rating, the better potential. The impact on performance is measured via the working time and its potential of reducing it. On the other hand, ergonomic assessments have an impact on working environment and should be managed as an individual assessment of the production system.

Result and Application of Sustainability of a Value Stream

The current state map for the value stream with the perspective of sustainability is shown in Figure 2. As in a traditional VSM, information flow is shown in the upper part of the figure, the material flow is shown in the middle, and measurements in the bottom part of the figure. Key performance indicators for the value stream is shown in table 1. The data collection of environmental and societal measures took longer time to understand and collect than the economic measures, which are known before by the company.

Especially the ergonomics assessment was hard to understand as no one in the data collection team had any expertise in ergonomics knowledge.

Discussion

The mapping of the value stream presented here is holistic in its approach and offers the possibility of process innovations regarding sustainability measures. Sustainability can be measured in a value stream by combining economic, environmental, and societal measures. Some of the measures are related to performance of the production system while ergonomic measures are related to work environment. From an operator point of view, the ergonomics measurements were seen as positive. Thus, operators have an interest in developing societal measures. From an executive point of view, the performance measures were easier to understand than societal measures. This may relate to the way executives are measured and how higher, more aggregated performance measures are set within the company. As the literature points out, the organizational model of a company impacts the way sustainability is developed internally. TitanX, the case company in this study, has already an organization that follows lean principles and thus both executive and worker involvement in place. The current state presented here is a pilot study where there is an improvement potential for involving workers and executives further for developing sustainability and integrate the measures on operational level. The result also indicates that there is a conflict of interests between economic, environmental, and societal measures.

Fig. 2 .

 2 Fig. 2. Value Stream Map for the SFI cooler

Table 1 .

 1 Key performance indicators for value stream of the SFI coolerResults of the ergonomics assessment at the value stream level is shown in table2and results of the ergonomics assessment at the task level is shown in

	KPI	Value
	Total lead time	1.75 weeks
	Value-added time	0.203 h
	Percentage value-added time	7.8 %
	Process water consumption	0.02 m3/product
	Raw material usage	8.3 kg/product
	Material utilization rate	78%
	Energy consumption	4.5 kWh/product

table 3 .

 3

Table 2 .

 2 Ergonomics assessment at the value stream level of the SFI cooler

	Ergonomics potential	5
	Variation in jobs	5

Table 3 .

 3 Ergonomics assessment at the task level in the value stream of the SFI cooler

		Manual Posture Force	Task
	Task	Working rating rating Category Time (s)
	Press 1	8.9	3	4	C
	Press 2	31.6	3	8	C
	Press 3	1.2	3	4	C
	Pre-assembly 1	32.4	3	3	E
	Pre-assembly 2	22.1	3	3	E
	Assembly	90.3	5	3	E
	Brazing	3.9	2	2	C and A
	De-assembly & polish	23	6	3	E
	Q control	5,5	3	3	E
	Packing	0,9	7	3	A and C


Kiwook Jung
email: kiwook.jung@nist.gov

Vittaldas Prabhu

Kai-Wen Tien

Boonserm Kulvatunyou

An Investigation to Manufacturing Analytical Services Composition Using the Analytical Target Cascading Method

Keywords: Factory design and improvement, Integration optimization, Analytical target cascading, Smart manufacturing, Services composition

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

Introduction

As cloud computing is increasingly adopted, the trend is to offer software functions, including analytical software functions, as modular services and compose them into larger, more meaningful ones [START_REF] Kulvatunyou | On Architecting and Composing Engineering Information Services to Enable Smart Manufacturing[END_REF][START_REF]Internet Web Site[END_REF]. The trend is attractive to analytical problems in the manufacturing system design and performance improvement domain because 1) finding a global optimization for the system is a complex problem; and 2) sub-problems are typically compartmentalized by the organizational structure. However, solving subproblems independently can result in a sub-optimal solution at the system level. This paper investigates the technique called Analytical Target Cascading (ATC) to coordinate the optimization of loosely-coupled sub-problems. Each sub-problem may be independently formulated by each stake-holding organization and be solved by modular analytical software services.

This study is motivated by the Factory Design and Improvement reference activity model developed in [START_REF] Choi | A Diagnosis and Evaluation Method for Strategic Planning and Systematic Design of a Virtual Factory in Smart Manufacturing Systems[END_REF]. The model decomposes major activities into subtasks and key decision-makings needed in a typical factory design and performance improvement project. It entails the needs for interactions across optimization problems at multiple control-levels.

For simplification of the illustration, this paper investigated the ability of ATC to coordinate three sub-problems at the manufacturing process control level including capacity design, lot sizing, and storage layout design. These three sub-problems are interlinked and typically dealt by different stakeholders. Their linkages are shown in Fig. 1.

Many analytical techniques have been developed to solve each of these three subproblems. These techniques are often used in isolation, but these problems are not independent. A change in one formulation can influence the outcomes and feasibilities of the other two. Therefore, capturing those dependencies and using them to integrate these three sub-problems is crucial.

ATC has been used to solve multidisciplinary-design-optimization problems that comprise heterogeneous sub-problems. These sub-problems are solved separately; but, each of their interim solutions is communicated regularly. This not only speeds convergence, it also gives a better solution than the one that is generated with no communication or one-way communication (such as in the hierarchical model in Fig. 1). The algorithm that ATC uses has been studied extensively and its convergence properties have been established mathematically [START_REF] Michelena | Convergence Properties of Analytical Target Cascading[END_REF]. The primary application of ATC has been in designing complex products such as automobiles and aircrafts [START_REF] Kim | Analytical Target Cascading in Automotive Vehicle Design[END_REF][START_REF] Allison | Analytical Target Cascading in Aircraft Design[END_REF]. Nevertheless, it has also been used in integrating supply chains and integrating marketing and production (DFM) [START_REF] Qu | Optimal Configuration of Assembly Supply Chains using Analytical Target Cascading[END_REF][START_REF] Michalek | Balancing Marketing and Manufacturing Objectives in Product Line Design[END_REF].

The result of this investigation indicates that ATC is a promising method in that it offers (1) easier management of the problem formulation of the overall system and (2) coherent, optimal solutions that can scale up to the size of the overall system by exploiting distributed and modular executions.

The rest of the paper is organized as follow. In Section 2, the analytical sub-problems are introduced; and it discusses drawbacks of the two traditional integration structures to compose these sub-problems: centralized and hierarchical. Then, the mathematical formulation of the proposed ATC-based collaborative structure illustrated in Fig. 1(c), is described in Section 3. In Section 4, we apply ATC to the sub-problems and analyze the results using data from a production project at Penn State [9]. Finally, the conclusion is presented in Section 5.

Composing Manufacturing Analytical Models

In this section, we introduce the three optimization sub-problems and their corresponding links. The exact links depend on the multi-criteria optimization of throughput (TH), inventory (INV), and work-in-process (WIP). Links can be seen as either common decision variables or input/output parameters, which are assumed to be non-negative. Note: π(•) is a penalty function which is used in the collaborative model and will be explained in section 3.1. In this section, we set it as a zero function.

Capacity Optimization

The important concern when optimizing capacity is that cycle times and WIP levels grow dramatically with increasing utilization [START_REF] Hopp | Factory Physics[END_REF]. Thus, the designers of this activity should decide on a reasonable throughput which minimizes the average WIP.

The important concern when optimizing capacity is that cycle times and WIP levels grow dramatically with increasing utilization [START_REF] Hopp | Factory Physics[END_REF]. Thus, the designers of this activity should decide on a reasonable throughput which minimizes the average WIP.

(P CP ) min z 1 (TH, WIP) = c w • WIP+π (TH, WIP) s.t. CT q = c 2 a + c 2 e 2 • u 1 -u • t e (1)
WIP = TH • CT q (2) u = TH • t e (3)
T H ≤ TH limit (4)
Where c w is the unit cost for holding one unit of WIP during the planning period, and π represents any penalty functions. Equation (1) represents the approximation of the waiting time in queue, CTq, in a G/G/1 system. The formulation shows that CT q is effected by the coefficient of variation (CV) of inter-arrival times c a , the CV of effective processing times c e , the utilization u, and the effective process time t e . The formulation can be generalized to multi-machine, multi-station systems. (2) represents the Little's law formula. [START_REF] Choi | A Diagnosis and Evaluation Method for Strategic Planning and Systematic Design of a Virtual Factory in Smart Manufacturing Systems[END_REF] shows the equation of utilization and (4) restricts TH.

Lot-Sizing Optimization

A wealth of models can be used for making lot-size decisions including EOQ (Economic Order Quantity) and EPL (Economic Production Lots) [START_REF] Hopp | Factory Physics[END_REF]. Here, we minimize the total inventory cost over T periods.

(P LS ) min z 2 (TH, INV) = T t=1 p t x t + h t i t + π (TH, INV) s.t. i t = x t + i t-1 -D t , ∀t = 1 . . . T (5)
x t ≤ TH•WH, ∀t = 1 . . . T (6)
x t + i t-1 ≤ INV, ∀t = 1 . . . T (7)
Where p t is the unit production cost and h t is the unit holding cost for period t. Equation ( 5) shows the inventory balance in each period, in which D t is the demand and x t is the production amount in period t. The constraint [START_REF] Allison | Analytical Target Cascading in Aircraft Design[END_REF] indicates the production amount should be less than capacity limit, in which WH is the available working hours during the period. Equation [START_REF] Qu | Optimal Configuration of Assembly Supply Chains using Analytical Target Cascading[END_REF] shows the inventory level should be less than INV.

Storage Layout Optimization

The storage layout sub-problem determines the optimal layout to minimize the material handling costs in terms of the distances 1) from WIP storage locations to locations of machines, and 2) between finished-goods inventory locations to the shipping docks. The storage layout problem is usually formulated as an assignment problem in which the storage floor is first subdivided into N grid squares and each item (WIP or INV) is assigned to a grid square.

(P S L ) min z 3 (INV, WIP) = N k=1 [c (w) k y (w) k + c ( f ) k y ( f ) k ]+π (INV, WIP) s.t. N k=1 y (w) k ≥ WIP (8) N k=1 y ( f ) k ≥ INV (9) y (w) j + y ( f ) j ≤ 1, ∀ j= 1, 2, . . . , N (10)
y (w) k , y ( f ) k ∈ {0, 1} (11)
Where c (w) k and c ( f ) k are the material handling cost for respectively storing one workin-process and inventory in the grid square k. y (w) k (y ( f ) k ) is a binary decision variable, which value is 1 if one unit of WIP (INV) is assigned to the grid square k. (8) and (9) represent the storage spaces demanded for WIP and INV, respectively. [START_REF] Hopp | Factory Physics[END_REF] restricts that one grid square can store only one unit of the items.

Centralized vs. Hierarchical Integration Structures

The centralized-structure approach, shown as Fig. 1(a), is an intuitive and coherent way to think about integrating the sub-problems. It results from minimizing the three objective functions of the sub-problems subject to all constraints (1) to (9). So, in essence there is only one, multi-objective function and one set of constraints. There are, however, two serious drawbacks associated with this centralized approach. First, is the issue of poor scalability of the approach in terms of the increasing number of decision variables and constraints. The other drawback occurs when reformulation of the model is needed, e.g., when the factory changes: essentially you basically have to start over.

The hierarchical-structure approach, shown in Fig. 1(b), reduces, but does not eliminate, the difficulty in addressing these two challenges. The sub-problems are solved individually, so reformulation is easier. Additionally, the sub-problems are typically solved in a prescribed order. That order is P CP , P LS , then P S L [START_REF] Michelena | Convergence Properties of Analytical Target Cascading[END_REF]. The links are directed links and are obtained as the outputs of the previously solved sub-problems. Clearly, this approach is not guaranteed to find a coherent, optimal solution. In addition, the quality of the final solution is highly dependent on the initial inputs to the initial process, P CP . Therefore, in practice, it requires many experiments, by varying the input conditions until an optimal solution is found across all the sub-problems!

Proposed Collaborative Approach

Our collaborative approach achieves both the high solution quality of the centralized approach as well as the reconfigurability of the hierarchical approach. The ATC algorithm connects sub-problems as if they were building-blocks. First, sub-problems at two ends of a link are assigned two specific roles: sender or receiver. Then, the link value in each sub-problem is replaced by two variables: target t i and response r i . The sender solves the target t i and the receiver solves the response variable r i within its own local variables and constraints. The ATC algorithm seeks to minimize the discrepancies between targets and responses with respect to the links. In this paper, as we said above, P CP is the sender of both WIP and TH; P LS is the receiver of TH and the sender of INV; and P S L is the receiver of both WIP and INV as Fig. 1(c).

The Collaboration strategy

In order to achieve global consistency, each of the three sub-problems is assigned a different penalty function. It "punishes" a sub-problem, by adding high costs to its objective function, when its solution violates consistency constraints. Realizing this, we decided to use the augmented Lagrangian as our penalty function and the basis for our collaboration strategy [START_REF] Tosserams | A Nonhierarchical Formulation of Analytical Target Cascading[END_REF]. The penalty function is shown in equation ( 12). Note that the notation "•" means the elementwise product for arrays.

π(•) = n t i=1 (v i t i + w i • (t i -r i ) 2 2 ) + n r j=1 (-v j r j + w j • t j -r j 2 2 ) ( 12
)
The Lagrangian penalty function includes two new variables, Lagrangian multiplier v i and quadratic penalty weight w i . They are updated in the outer loop of ATC. The updating methods are expressed below, where l represents the iteration of the ATC algorithm.

v i (l + 1) = v i (l) + w i (l) • w i (l) • (t i (l) -r i (l)) ( 13
)
w i (l + 1) = β • w i (l) (14)
The ATC algorithm has three main steps:

Step 1: Inner loop -solving sub-problems separately and updating the target and response variables.

Step 2: Outer loop -updating the Lagrangian multipliers and weights via expression (13) and ( 14).

Step 3: Termination -terminating the algorithm when the discrepancies of all target and response pairs are smaller than a given tolerance.

Reconfigurability and Discrepancy Visualization

As mentioned in the previous section, the ATC algorithm connects the sub-problems through target and response variables. It has the advantage of reusability. Suppose, for instance, a company wants to replace their current EOQ sub-problem with a (Q, r) subproblem for lot-sizing design; the other two sub-problems are still reusable. Furthermore, since the overall system-problem has been partitioned into three sub-problems, the structural complexity of the overall system is reduced. Stakeholders of each subproblem can also formulate their problems independently; therefore, the factory design and performance improve project can progress efficiently.

The ATC approach also allows feasibility issues across sub-problems to be conveniently resolved. It monitors the target/response values and showing the discrepancies between differing objectives in sub-models. For example, if there was a space reduction made in P S L problem causing the responses r WIP and r INV not meeting the targets given by the other two sub-problems. The discrepancy can be shown in the results. This allows for the stakeholders to effectively collaborate and resolve the specific conflict.

Case Study

We use the IME Inc. project [9] to demonstrate the potential benefits of our collaborative approach over the other two. The aluminum chess set is the primary product in this case study. The associated process plan includes only one turning center and 240 labor hours.

In addition, the product will be delivered to customers at the end of each quarter (March 31th, June 30th, etc.). Note, this knowledge could be used to determine the minimum value for storage size. That minimum value has to be large enough to store both WIPs and finished products during that time. Table 1 shows the parameters for the design subproblems. c a is approximated by the variance of the demand and c e is significant because of the long set-up time of this product. t e represents the effective processing time for the whole chess set. The production costs p t changes because of the fluctuation of material costs. The holding cost for one set per one week is estimated by the typical interest rate per quarter (about 6.25%) times the production costs. The factory has 150×75 (cm 2 ) area for both WIP and the finished products (see Fig. 2). A finished product is wrapped into a 15×7.5×7.5 (cm 3 ) box. Moreover, the boxes cannot be piled up because of the strength of the boxes. Hence, the storage area is divided into a grid of 100 squares, each of which can store only one box or one working-in-process. The material handling cost of a finished product at a certain location is calculated by multiplying the unit operation cost with the rectangular distance between the machine and the exit dock. With a technician's suggestion, we assume the unit costs of the material handling costs is $0.01/2.5 centimeter. The desired throughput (initial value) is determined by the average demand rate 0.43 sets/hr. The three models were constructed and run in MATLAB 2015a. The collaborative model was terminated after 96 iterations, resulting in a tolerance value of 10E-6 for the discrepancies between sub-problems. When terminated, w = (1, 1, 1) and v = (-3.75, 1.34, 1.76). The results show that the proposed collaborative approach can find the same solution as overall optimal solution generated by the centralized approach, but the hierarchical approach cannot. However, the computation time of the collaborative model is much larger than those of the other two (less than 5 seconds). This implies that the collaborative model is more suitable for solving problems in the factory "design stage," where the system complexity issue is much more critical than the computational time. Nevertheless, a parallel computing model could be explored to speed up the solver to provide a solution in a near real-time.

Conclusion

In this paper, we proposed a collaborative approach, called Analytical Target Cascading (ATC), to composing analytical sub-problems and possibly associated software services to meet the overall objective. Our experiment shows a promising result. Sub-problems can be formulated and executed modularly and possibly under a distributed computing scheme. Even so, ATC connects these sub-problems and has the capability to achieve the coherent optimal as in the centralized model. Furthermore, unlike the centralized approach, our approach allows sub-problems to be changed or improved easily. Moreover, the discrepancies between targets and responses in each sub-problem are visible allowing for feasibility issues to be easily resolved. In the future work, we are planning to integrate control-level problems and design-level problems.

Fig. 1 .

 1 Fig. 1. Search methodology

Fig. 2 .

 2 Fig. 2. Factory layout

4 8290. 5 (Fig. 3 .

 53 Fig. 3. The storage layouts

Table 1 .

 1 The parameters of sub-problems

	P CP Sub-problem P LS Sub-problem (Quarterly Plan) P S L Sub-problem
	c a	0.685	p t ($/sets) (20.0, 25.0, 18.0, 20.0)	Area (cm 2 )	(150, 75)
	c e	0.942	h t ($/sets) (1.25, 1.56, 1.13, 1.25)	Box (cm 2 )	(15, 7.5)
	t e (hrs) 1.388	D t (sets) (100, 80, 130, 90)	Unit cost ($/cm) 0.01
	c w ($) 4	WH(hrs) 240

Table 2 .

 2 The computational results

		Centralized model Hierarchical model	Collaborative model
	Comp Time (sec)	4.9176	0.0742	132.7390
	Total Cost ($)	8290.5	8388.

Acknowledgement: The work described in this paper was funded in part by NIST cooperative agreement with Penn State University No. 70NANB14H255. Disclaimer Any mention of commercial products is for information only; it does not imply recommendation or endorsement by NIST.


Jannicke Baalsrud Hauge

Stefan Wiesner

Ioana A Stefan
email: ioana.stanescu@ats.com.ro

Antoniu Stefan
email: antoniu.stefan@ats.com.ro

Klaus-Dieter Thoben

Applying Gamification for Developing Formal Knowledge Models: Challenges and Requirements

Keywords: Gamification, Knowledge capturing, Product Service System

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

Introduction

Nowadays, the field of systems engineering is influenced by rapid technological change and ever growing competition. In order to be the first to react on market trends, methodologies like concurrent engineering (CE) are introduced to shorten development cycles and reduce "time to market" [START_REF] Corsetti | Complex Systems Developed with System Concurrent Engineering[END_REF][START_REF] Chang | Customer Requirements Elicitation and Management for Product Conceptualization[END_REF]. However, just being fast is not sufficient; additionally, the system has to be both appropriate and cost effective [START_REF] Kossiakoff | Systems engineering principles and practice[END_REF]. Customers demand integrated solutions and services, covering the whole system life cycle, from ideation to decommission, thus more and more companies are evolving their business activities to form product-service-systems. These systems are complex and dynamic and their requirements evolve in time. The already existing knowledge (either on existing products, and services or just related to the ideas never brought to the market) is often distributed among employees, and different departments in an organization do often have different requirements.

Requirements define the needs of organizations, groups, or people along with their surroundings, and describe what a solution must offer in order to satisfy those needs. Their formulation, documentation and maintenance are the main objectives of requirements engineering (RE). It describes "a process, in which the needs of one or many stakeholders and their environment are determined to find the solution for a specific problem" [START_REF] Nuseibeh | Requirements Engineering: A Roadmap[END_REF]. Inadequate RE is one of the main sources for the failure of development projects and culminates in exceeding budgets, missing functionalities or even the abortion of the project [START_REF] Hauksdóttir | Identification of a Reusable Requirements Structure for Embedded Products in a Dynamic Market Environment[END_REF][START_REF] Boehm | Software Defect Reduction Top 10 List[END_REF]. For complex systems this requires that the knowledge within the organisation can be captured and transferred. Within complex systems, as well as for product development, participatory or co-creative design approaches are often used in order to involve stakeholders in the decision-making process at early stage in order to ensure that the developed system is in line with their needs. The same approaches can also be used in order to capture the knowledge existing in the organisation, but it requires that there is a tool that is able to capture the knowledge, as well as involving the right people. This might also lead to a better usage of resources. From a technical point of view this integration can be realized today focusing on reusability of components [START_REF] Hauksdóttir | Identification of a Reusable Requirements Structure for Embedded Products in a Dynamic Market Environment[END_REF] as well as through better collaboration across different process steps [START_REF] Boehm | Software Defect Reduction Top 10 List[END_REF].

The required competencies for system development and support in other life cycle phases are included through collaboration with partners from different domains [START_REF] Blanchard | System Engineering Management[END_REF]. This increases both the number of stakeholders involved in systems engineering and the complexity of the system itself. Consequently, understanding what the customer and the other affected stakeholders expect from the system, i.e. their underlying needs, and linking information from all phases of the life cycle to the development process is a prerequisite for successful systems engineering [START_REF] Sage | Handbook of Systems Engineering and Management[END_REF][START_REF] Elgh | Modelling and Management of Manufacturing Requirements in Design Automation Systems[END_REF][START_REF] Nilsson | Managing Stakeholder Requirements in a Product Modelling System[END_REF]. This represents however a challenge, since much of the knowledge is not formalized and unstructured, thus difficult to retrieve and process.

Previous work [START_REF] Kosmadoudi | Harmonizing Interoperability -Emergent serious gaming in playful stochastic CAD environments[END_REF][START_REF] Hesmer | Supporting the Ideation Processes by a Collaborative Online Based Toolset[END_REF] has highlighted that sustainable adaptation and integration of game design elements into engineering systems can be a good approach for both increasing the process innovation as well as to help collecting information from complex processes. However, [START_REF] Kosmadoudi | Harmonizing Interoperability -Emergent serious gaming in playful stochastic CAD environments[END_REF] also show that further analysis of the enabling mechanisms as well as on how to capture the knowledge are needed. A more detailed analysis of the challenges shows that accommodation of gamification concepts, mechanics and components into engineering systems implies substantial modifications of these systems. A key is here the development of the knowledge models. One of the main challenges in developing formal knowledge models is to efficiently elicit knowledge from distributed resources and form a coherent body of knowledge that can be validated and extended by user communities.

This paper builds upon the perspective where gamification supports knowledge processes using a participatory and gamified approach for complex engineering processes like the requirement engineering of PSS.

Methodology

The methodological approach is based on combination of research methods. A literature review was carried out targeting gamification, knowledge processes, and information on engineering applications like PSS and supporting technologies. Scientific papers were accessed through Scopus searching for associated key words [START_REF] Kitchenham | Systematic literature reviews in software engineering 'A systematic literature review[END_REF] The relevance of the downloaded papers for this article was based on assessing the abstract, as well as by searching for the combination of gamification and mechanisms in the full papers. The first search based on abstracts followed by a refined search. As several expressions are used in literature to describe the PSS concept, we applied TITLE-ABS-KEY ("product-service" OR PSS OR IPS OR "Extended Product") as the first search term, combined with AND TITLE-ABS-KEY ("knowledge management" OR "knowledge sharing") as the second term. This resulted in 214 identified abstract and the refine search identified 40 articles. The search related to gamification of engineering applications was carried out using the ("ENGINEERING APPLICATION" AND ("GAMIFICATION" OR "SERIOUS GAMES" OR "SIMULATION".)). This resulted in 369 abstracts. Adding the same key words as in the definition search resulted in only identifying 15 articles that could be considered of being relevant.

The work with the specific engineering applications and the gamification had a different methodical approach. The researchers have been involved in the specifications and development of the scenarios. Design Science was the overall scientific approach in this work [START_REF] Kuechler | Promoting relevance in IS research: an informing system for design science research[END_REF][START_REF] Pries-Heje | Strategies for design science research evaluation[END_REF], so action research was applied [START_REF] Sein | Action Design Research[END_REF].

Characteristics of a PSS

In order to capture the knowledge needed for a RE approach for PSS, it is necessary to identify the specific characteristics of such systems. In the following, some widely used definitions of PSS found in the literature are analyzed for these characteristics.

"A Product Service system (PS system) is a marketable set of products and services capable of jointly fulfilling a user's need. The PS system is provided by either a single company or by an alliance of companies. It can enclose products (or just one) plus additional services. It can enclose a service plus an additional product. And product and service can be equally important for the function fulfilment. The researcher's need and aim determine the level of hierarchy, system boundaries and the system element's relations" [START_REF] Goedkoop | Ministry of Housing, Spatial Planning and the Environment[END_REF] .

"A PSS is an integrated product and service offering that delivers value in use. A PSS offers the opportunity to decouple economic success from material consumption and hence reduce the environmental impact of economic activity. The PSS logic is premised on utilizing the knowledge of the designer-manufacturer to both increase value as an output and decrease material and other costs as an input to a system" [START_REF] Baines | Stateof-the-art in product-service systems[END_REF] .

"'An Industrial Product-Service System is characterized by the integrated and mutually determined planning, development, provision and use of product and service shares including its immanent software components in Business-to-Business applications and represents a knowledge-intensive socio-technical system'….

IPS 2 enable innovative function-, availability-or result-oriented business models" [START_REF] Meier | Industrial Product-Service Systems-IPS2[END_REF] .

The analysis of the above definitions reveals some characteristics that seem to be specific for PSS in general. These characteristics are listed below: ─ Integration of product and service shares, including software components; ─ Mutual planning, development, provision and use of product and service shares; ─ Fulfilling an end user need by delivering value in use; ─ Provided by either a single company or by an alliance of companies; ─ Dynamic adoption of changing customer demands and provider abilities; ─ Enabling innovative function-, availability-or result-oriented business models. The characteristics shows the complexity of PSS, thus defining the requirements and the system specification are challenging. The next section therefore looks at how a participatory design approach can be used for supporting the challenging task

Participatory Design Approach

Knowledge capturing remains a compelling case for organizations, especially because knowledge is a dynamic asset that continually must be updated, revised, and built on to maintain a valid base 20 and value. Furthermore, it is a challenge that a lot of the information is not formalized, and thus it is difficult to capture with current tools. To address this challenge, the authors have considered key knowledge-centric drivers that apply to organizations, regardless of their industry 21.

─ The failure of organizations to know what they already know; ─ The emergent need for smart knowledge distribution; ─ Knowledge velocity. ─ The issue of knowledge walkouts and high dependence on tacit knowledge. ─ The need to deal with knowledge-hoarding propensity among employees. ─ A need for systemic unlearning.

Highly interconnected systems like smart manufacturing systems need to be explained and managed across many layers -technological, social, data, human and institutional [START_REF] Palfrey | Interop: The Promise and Perils of Highly Interconnected Systems[END_REF]. Further, in the absence of suitable analytical and formal tools, institutions within complex systems take decision based on heuristics. Such heuristics contain significant knowledge both about the stakeholders' perspectives on the systems and on their management strategies. These heuristics needs to be collected in some form to overcome limitations and embed local institutional knowledge in formal tools. This implies that the development of these models and tools should be done in a participatory manner, to ensure all stakeholders collectively develop and reach an understanding of the model. Such participatory methods, in conjunction with these complex models and tools also support model validation. Simulation Gaming provides ways to collectively decide on the problem formulation, system boundaries and on the dynamics of the system that will be addressed.

By implementing adaptable and customizable gamified SMEs that support knowledge management, the organization will be able to plan and implement activities that stimulate employee interest and participation 20, and that enables them to benefit of a wide range of opportunities. The challenge in the knowledge capturing part of PSS and manufacturing application is that much of the information is not formalized and not structured. The next section discusses under which circumstances gamification of an application can support the knowledge gathering and improve the knowledge model.

Gamification of Manufacturing Environments: Requirements on Concept and Challenges

Gamification consists of using game-based elements and mechanisms in non-game environments with the purpose of employing the motivational properties of games [START_REF] Wood | Gamification[END_REF]. Gamification as a method has be criticized, and there are some drawbacks like the manipulation aspect [START_REF] Kapp | The Gamification of Learning and Instruction Fieldbook: Ideas into Practice[END_REF]. A simple addition of gamifying elements does not automatically translate into the desired outcomes, so gamification components and elements need to be designed and adapted to the context they are applied to. To do so, it is necessary to establish clear goals, incremental goals and rewards, mechanisms of progression, intermediary and final statuses, etc.

Another key challenge concerns the actual incorporation of gamification processes into existing application, which is a complex task even for experienced developers. Integration of gamification mechanisms carried out by manufacturing environments' developers can answer to some of the above-mentioned issues. However, these environments do not fully benefit of the potential of gamification mechanisms, as identified by Wood [START_REF] Wood | Gamification[END_REF], if such systems do not allow tutors/ users customize their working environments. Users are not actively involved in the SMEs architecture and this limits their capabilities and abilities to perform better. Moreover, the emergence of new technologies requires new approaches and more flexible solutions for integration, empowering users to customize.

Based on the consideration above, a gamified manufacturing environment that aims at capturing, process and feed a formal model need to have the following characteristics: ─ Recognition and reward systems for outstanding individual contributions at a project or the organization level. ─ Examples and best practices can be extracted from tracked gameplay. ─ Recurring challenges that employees are experiencing can be identified and addressed. ─ Contextual knowledge reuse is automatically supported, and knowledge transfer can potentially impact all PSS users. ─ Exploit the added value of social knowledge through a gamified approach that enables people to discover and share knowledge. ─ Access to personalized working environments is enabled.

We are currently working on the gamification of engineering process for knowledge capturing. The gamification is realized in Unity. It mirrors the main processes for future PSS system. It is designed as a gamification of the requirements elicitation process. Even though it uses role playing mechanisms, each player plays they normal position in the company. The example below explains one of three case studies where we have carried out the beta testing, so still in progress.

In the given example, the task is to decide which requirements future PSS need to fulfil within the manufacturing of office furniture. In this example the 3D model of the office of the service providers was important into the Unity engine directly. In a second step a narrative story line, describing the main steps of the requirements elicitation process was added and game elements like time restriction and rewards were applied. The gamification is facilitated and uses creativity methods like adapted versions of six thinking hats etc.

The beta test was carried out Mid-June 2016 with 6 different participants covering all the involved stakeholders' groups. It was set up as a workshop of 2x2h. The first initial results showed that the gamification of the environment helped in analyzing the existing requirements (collected using a traditional method) from different perspectives and to refine these. These first set of stakeholder requirements were related to ─ Support for collaboration between the stakeholder ─ Business models for servitisation ─ Measurement and assessment of brand value and sales bids ─ Integration of technologies like sensor and ─ Feedback integration either via data analytics or customer/employee ─ Interface design For the more concrete applications (i.e. how to integrate sensors and how to use data for a new service), the gamification supported the process sufficiently according to the participants, and the collected outcome regarding capturing more details of the system was achieved. However, the current gamification showed some weaknesses related to the support on more abstract requirements like future business models. The gamification clearly showed some limitations here, so that it we did not capture much of the participants' knowledge here in one of the group. In the second group, this worked better. Why this problem occurred needs further investigation.

Conclusion

The paper describes the challenges of generating a formal modal and capture knowledge in a simulation game built using previously developed tools. The authors discuss the characteristics of PSSs and the participatory design approach, with the purpose of supporting the implementation of gamification mechanisms in manufacturing environments.

Technology reshapes the world we learn, work, and live in. New levels of interaction between men and machine have become possible and more widespread, opening the way towards reliable, sustainable, technology-driven ecosystems.

The growth, maturation, and widespread adoption of technologies have the potential to disrupt and innovate, and offers new opportunities for data collection and retrieval. This paper discusses the current challenges of PSS and the potential of gamification to enhance knowledge processes and user interface in PSS. Present and future scenarios are presented to reflect how gamification can impact current and future systems of systems. The concept of a gamification tool is introduced as a mean to streamline knowledge processes and enable PSS tutors/ users to directly adapt and personalize PSS to better answer their needs Future work will explore the integration of digital gams into PSS, exploring key challenges in terms of standardization and interoperability, as well as advances in hardware and software to discover new opportunities for enhancing user experiences and outcomes.

Acknowledgements. This work has been funded by the European Commission through the Projects PSYMBIOSYS: Product-Service sYMBIOtic SYStems (No. 636804) and BEACONING (No. 687676). The authors wish to acknowledge the Commission and all the project partners for their contribution.