Bruno A Rodrigues Filho
email: bafilho@inmetro.gov.br

Rodrigo F Gonçalves

Measuring the economic impact of metrological frauds in trade metrology using an Input-Output Model

Keywords: Legal metrology, economic distortion, market asymmetry, Leontief

The present study aims to evaluate the economic distortion in trade metrology due to metrological frauds in measuring instruments used in the commerce and industry. The economic distortion represents the economic losses due to measurement deviations in trade. An Input-Output Model approach is carried out in order to determine the economic distortion whenever an output in a process represents the input to another one and it considers the aggregation of values of products traded in the economy. A case test is also conducted using empirical data of measurement errors and metrological frauds in the fuel sector in Brazil in order to determine their economic impact. The results show that the impact of metrological frauds increase the distortion uncertainty from US$ 54,910,307.13 to US$ 303,734,309.35 toward consumers' losses creating a great asymmetry in the market.

Introduction

The commerce has always been present in the human history and it is not possible to imagine our society separately from it. Specifically, the commerce involving goods which values are based on weights and measures has always been present in people's everyday life. Initially, weights and measures were initially introduced to control food in trade [START_REF] Birch | The Expanding Scope of Legal Metrology and The Changing Role of The State in A Globalised World[END_REF] and the origins of the weighing instruments which are a symbol of parity, truth and justice date back to the oldest cultures 10,000 years ago [START_REF] Euler | History of Scales Part 15: Automatic Gravimetric Filling Instruments (Agfis) -Weighing and Bag Filling Machines for Loose Bulk Products[END_REF].

The necessity for protection regards on the economic distortion or market asymmetry that is describe as the monetary value associated to a measurement deviation due to the inaccuracies intrinsic to the measuring processes as a consequence of errors, uncertainties, operator's inaccuracy, environmental conditions and others.

This economic distortion impacts both economy and society since deviations between buyers and sellers cause economic losses and unfair competition. Moreover consumer's protections aspects are also related to this market asymmetry that may be an indicator of the economic impact of legal metrology [START_REF] Rodrigues Filho | Legal Metrology, The Economy and Society: A Systematic Literature Review[END_REF]. Several researchers have also presented the importance of legal metrology and its social and economical impact to the society, trade, industry and governments [START_REF] Stiefel | Management Assistance for Weights and Measures Progress, Measuring Inaccuracy's Economic Distortion[END_REF][START_REF] Birch | Benefit of Legal Metrology for The Economy and Society -A Study for The International Committee of Legal Metrology[END_REF][START_REF] Kochsiek | Modernization of Legal Metrology in Germany[END_REF][START_REF] Leitão | Contramedidas De Hardware Y Software Sobre El Fraude De Alta Tecnología Al Surtidor De Combustible Bajo El Alcance De Metrología Legal[END_REF][START_REF] Leontief | Structure of The World Economy: Outline of A Simple Input-Output Formulation[END_REF]. The initiative regarding using empirical data do evaluate the economic impact of inaccuracy of measuring instruments was initially proposed during the decade of 1970 [START_REF] Stiefel | Management Assistance for Weights and Measures Progress, Measuring Inaccuracy's Economic Distortion[END_REF] and several formulations using proxy variables have also been proposed, such as [START_REF] Birch | Benefit of Legal Metrology for The Economy and Society -A Study for The International Committee of Legal Metrology[END_REF]: number of measurement related patents in comparison to the total; cost of certification as an indicator of industries willingness to pay for reliability; the sum of all industry equipment.

Despite the deviations of the measuring instruments regards to the measurement error theory, an intentional error or a metrological fraud caused by the operator in order to prejudice a buyer in a commercial transaction creates a great distortion in the economy. An example is the energy market in Germany, where the global competition has led to tighter profit margins increasing the risk for metrological frauds [START_REF] Kochsiek | Modernization of Legal Metrology in Germany[END_REF]. Recently, the global market has also been overflowed by metrological frauds in the fuel market occasioning severe losses to the buyers and competitors [START_REF] Leitão | Contramedidas De Hardware Y Software Sobre El Fraude De Alta Tecnología Al Surtidor De Combustible Bajo El Alcance De Metrología Legal[END_REF].

Regardless of the obvious aspect that a metrological fraud is prejudicial to the consumers and consequently the economy, its economic impact is not well known. The Input-Output Model allows to compute how a change in a product demand impacts its production contemplating the interconnections of productive processes since it considers that an output of a process can be an input to another one [START_REF] Leontief | Structure of The World Economy: Outline of A Simple Input-Output Formulation[END_REF].

Consequently, the Input-Output Model, hereinafter called I-O for simplicity, permits to evaluate the economic impact a measurement deviation in a product to the economy, introducing a factor representing these deviations to the traditional Leontief's formulation, identifying how the deviations spreads across every sector on the economy.

Then, based on the I-O theory, the present study aims to evaluate the economical uncertainties cause by metrological frauds in trade. The measurement errors report for fuel disperses in the field in Brazil is used to provide an empirical case. In order to understand the impact of metrological frauds, we replaced a percentage of the empirical deviations by values based on known metrological frauds to evaluate the behavior of these frauds to the economy.

Methodology

Formulation to compute the economic distortion

The I-O formulation is based on the assumption that the productive processes are connected since an input of a process is the output of another process [START_REF] Leontief | Structure of The World Economy: Outline of A Simple Input-Output Formulation[END_REF]. This interconnection is represented in a matrix system where the lines represent the outputs and columns the inputs. The basic conception is given by the product output 𝑞, which is represented by the final demand of products 𝐹 plus the intermediate consumption of industries 𝑈, as seen in [START_REF] Birch | The Expanding Scope of Legal Metrology and The Changing Role of The State in A Globalised World[END_REF].

𝑞 = 𝑈 + 𝐹 (1)
Due to linear algebra, the basic formulation of the I-O is given by ( 2), where g represents aggregation of q in industry sectors, I the identity, and D and B are coefficient matrices.

𝑔 = (𝐼 -𝐷. 𝐵) -1 . 𝐷. 𝐹 (2)
Consequently, the total national production of the n aggregate products g is given by the sum of the vector g, as shown in [START_REF] Euler | History of Scales Part 15: Automatic Gravimetric Filling Instruments (Agfis) -Weighing and Bag Filling Machines for Loose Bulk Products[END_REF], where g is given in monetary units.

𝒈 = ∑ 𝑔 𝑖 𝑛 𝑖=1

(3)

To compute the impact of measurement deviation, a multiplier factor 𝛿 representing a percentage of deviation due to measurement errors is introduced in both intermediate consumption of industries and the final demand, as seen in ( 4).

𝑞′ = 𝛿. 𝑈 + 𝛿. 𝐹 (4)
Finally, the influence of the distortion due to measurement deviations, i.e. the economic distortion ED, is given by the difference of total production including 𝛿, 𝑔′ less the total production of the n aggregate products 𝑔, as shown in [START_REF] Rodrigues Filho | Legal Metrology, The Economy and Society: A Systematic Literature Review[END_REF].

𝐸𝐷 = ∑ (𝑔′ 𝑖 𝑛 𝑖=1 -𝑔 𝑖 ) (5)

Evaluating the impact of metrological frauds

A metrological fraud can be understood as an intentional deviation introduced in a measuring instrument to promote financial gains to the seller over the buyer. The definition of measurement error is given in [START_REF] Kochsiek | Modernization of Legal Metrology in Germany[END_REF], where the error e is equal to the instrument value 𝑒 𝑖 less the value of the standard used for comparison 𝑒 𝑠 .

𝒆 = 𝑒 𝑖 -𝑒 𝑠 (6)
Consequently, positive values of e represent buyer' losses and negative values seller's losses. For example, in the fuel market, for a petro pump displaying 20.10l and the standard displaying 20.00 l, and for 1l = $1.00, it would represent a loss of $0.10 for the buyer.

Since the measurement deviations of instruments can be represented by an average and measurement uncertainty regarding a statistical distribution, the economy distortion must also contain an uncertainty. For the present study it is reasonable to assume that measurement errors of the instruments used in the market and industry follow a gauss distribution. We also assumed the standard deviation to represent the measurement uncertainty in the present study.

However, the set of illegal devices would follow a different statistical distribution once they are intentionally regulated to provide higher positive measurement errors. Thus, the contributions of fraudulent devices contribute only to positive values of deviations. So in order to analyze the contributions of errors to the economic distortion uncertainty, we considered the mutual distribution uncertainty to positive values (buyer's losses) and the regular devices distribution to negative values (seller's losses), as seen in figure 1. A mutual distribution uncertainty 𝜎 𝐷𝑀 is obtained combining deviations of both fraudulent and regular measurement instruments distributions. The measurement uncertainty is represented in [START_REF] Leitão | Contramedidas De Hardware Y Software Sobre El Fraude De Alta Tecnología Al Surtidor De Combustible Bajo El Alcance De Metrología Legal[END_REF], where 𝑎 𝐷𝑀 represents the average of the mutual distribution, 𝑎 𝐷 the average and 𝜎 𝐷 the standard deviation of the instruments distribution.

𝜎 𝐷 -𝑎 𝐷 ≤ 𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑚𝑒𝑛𝑡 𝑢𝑛𝑐𝑒𝑟𝑡𝑎𝑖𝑛𝑡𝑦 ≤ 𝑎 𝐷𝑀 + 𝜎 𝐷𝑀 (7)

Simulating a metrological fraud

In order to evaluate the economic impact of metrological fraud we used an empirical database of measurement errors for automotive ethanol dispensers in Brazil [START_REF] Rodrigues Filho | Information Systems as A Tool to Improve Legal Metrology Activities[END_REF]. And, the metrological frauds for the fuel market usually varies from 6% to 12% [START_REF] Leitão | Contramedidas De Hardware Y Software Sobre El Fraude De Alta Tecnología Al Surtidor De Combustible Bajo El Alcance De Metrología Legal[END_REF].

To analyze how the economic distortion behaves when fraudulent instruments are used in the commerce, we have established two variables: the percentage of fraudulent devices and the measurement error due to the fraud. Then, a Scilab 5.5.2 algorithm replaces randomly a percentage of instruments in the database by fraudulent values, as follow: Sheets=readxls('Ethanol_Error.xls') // Reading empirical data typeof(Sheets) Error=Sheets( 1) typeof(Error) Error.value() percentage=0.05//% Defining percentage to be replaced total=fix(37719*percentage/100)+1 fraudError=Error.value() VolumeFraud=2000 //ml for i=1:total //Replacing values fraudError((fix(37719*rand())+1))=VolumeFraud end write_csv(fraudError,"Fraud_Error.xls") //new dataset//End The empirical data of measurement errors of automotive ethanol dispersers where the average (aD) and the standard deviation (D) comprising 37,719 ethanol dispensers verified in 2014 are represented in ml units by: aD = 4.22; D = 40.83. The great divergence of these dispensers is mainly caused by the imprecisions of the measurement of fuel, such as environmental conditions, humidity, user's proficiency and others [START_REF] Batista | Comparison on The Verification of Fuel Dispensers[END_REF].

Finally, to compute the economic distortion according to 5, we used the latest published Brazilian Input-Output matrices representing the economy in 2005 [START_REF]Rio de Janeiro[END_REF] as well as the dollar exchange rate [12]: US$ 1.0000 = R$ 2.3407.

Results

For a bigger percentage of fraudulent devices used in trade, the economic distortion associated to the measurement errors is consequently bigger. Table 1 shows the results of economic distortion from a range of 0.01% to 1% of fraudulent measuring instruments introduced in the commerce comparing to a scenario where no frauds are used. A fraud value of 10% is applied to the results presented in table 1, representing a deviation of 2 l for each 20 l traded.

The measurement uncertainty regarding seller's losses remains constant once a fraud affects only the buyers. The average representing the economic distortion is linear dependent of the percentage of fraudulent devices (R 2 = 0.9998). Figure 3 shows the economic distortion variation due to metrological frauds, displaying the measurement uncertainty. It is also possible to observe the great divergence between consumer and seller's losses. The economic distortion for bigger percentage values of fraudulent instruments in the market introduces bigger consumers' losses differently when comparing to the sellers' losses, which remains constant. As a direct consequence, the probability of consumers' losses is bigger than sellers' and it indicates a component of unfair competition caused by the asymmetry of information. The range of US$ 352,970,762.60 uncertainty caused by 1% of irregular instruments in the commerce is more than three times bigger than the range of uncertainty if no fraudulent instruments were used and the uncertainty toward consumer's losses is six times bigger than the initial uncertainty, where no fraud is applied to the market.

In order to identify the behavior of the economic distortion due to the volume fraud dispensed to the consumers, we simulated the economic distortion for a constant number of fraudulent instruments and ranged the value of fraud, from 500 m l to 5000 m l for each 20 l traded. Figure 4 shows the behavior of the economic distortion for different values of fraud when keeping the percentage of 0.01% fraudulent instruments in the market constant.

The economic distortion introduced in the economy increases the consumers' losses in the trade due to bigger errors of volume dispensed. The dependence between the economic distortion and the fraudulent measurement values is linear, for R 2 =0.9998.

Conclusion

The Input-Output Model allowed us to compute the economic distortion due to the measurement errors of instruments used in trade contemplating the interconnections of the sector on the economy. Since a fraud is intentionally introduced in the market it changes the random behavior of deviations and add a systematic deviation component, which reflects in the economic impact to the economy. The methodology proposed to compute the impact of fraudulent devices in the market also permitted to identify their impact on the economy based on two variables: the percentage error of measurement traded and percentage of fraudulent instruments.

Empirical information of the fuel market in Brazil also enable to evaluate the impact of metrological frauds showed to be expressive and it increases the range of uncertainty of the economic distortion from US$ 104,146,760.38 to US$ 352,970,762.60 toward consumers' losses, for 1% of fraudulent devices for a 10% deviation. The uncertainty representing buyer's losses increases from US$ 54,910,307.13 to $ 303,734,309.35 creating a big asymmetry between buyers and sellers in the market. Moreover, we identified that the economic loss is linearly dependent of the volume deviation introduced in the instrument, for a constant number of fraudulent devices.

The big impact of metrological frauds in the commerce may affect the relation between buyer and seller due to the great asymmetry of information caused by the intentional deviation in the measurements, creating unfair competition that may also impact honest sellers leading the economy to a failure.

Additionally, the proposed model can also be applied to any industry's quality management system in order to evaluate the losses due to the measurement processes since the I-O analysis is a consolidate model in economy.

Fig. 1 .

 1 Fig. 1. Uncertainty evaluation for the economic distortion.

Figure 2

 2 Figure 2 also illustrates the process of simulating fraudulent instruments in the market.

Fig. 2 .

 2 Fig. 2. Process for replacing empirical measurement errors for simulated defrauded values.

Fig. 3 .

 3 Fig. 3. Effect of metrological frauds on the economy according to the percentage of fraudulent instruments.

Fig. 4 .

 4 Fig. 4. Economic distortion for a constant number of fraudulent devices and volume variation.

Table 1 .

 1 The variation of the measurement uncertainty according to the percentage of fraudulent devices for a 10% volume deviation.

	% of fraudulent	Economic	Measurement Uncertainty
	instruments in the market	Distortion Average (US$)	Buyer loss	Seller loss	Range (Buyer + Seller)
	0	$ 5,673,853.89	$ 54,910,307.13		$ 104,146,760.38
	0.01	$5,969,647.42	$ 67,441,271.42		$ 116,677,724.66
	0.05	$7,018,370.10	$ 88,496,693.13	$ 49,236,453.24	$ 137,733,146.37
	0.1	$7,018,370.10	$ 109,686,654.24		$ 158,923,107.49
	0.5	$19,119,034.64	$ 216,363,722.30		$ 265,600,175.55
	1	$32,295,351.86	$ 303,734,309.35		$ 352,970,762.60

Acknowledgement

The authors acknowledge the support of INMETRO, which enabled us to carry out this research.


Stefan Wiesner

Jannicke Baalsrud Hauge

Florian Haase

Klaus-Dieter Thoben

Supporting the Requirements Elicitation Process for Cyber-physical Product-Service Systems Through a Gamified Approach

Keywords: Requirements elicitation, , Product-service systems, Cyberphysical systems, Serious games

Solutions are offered more and more in the form of Product-Service Systems (PSS), which combine tangible and intangible components into a comprehensive package for the customer. The rise of Internet of Things technology enables new ways of integrating products and services. So-called Cyber-Physical Systems (CPS) include the necessary sensors, actuators and software to provide reconfigurable functionalities for changing demands. However, engineering complexity is increased by the evolutionary aspect, as well as the increased number of stakeholders and system components involved over the whole life cycle. Understanding the underlying requirements is fundamental to establish a common perception of the targeted system among the manufacturer, service providers and the other stakeholders. This paper presents a gamified approach to elicit stakeholder requirements for the development of these complex systems. Four industrial users will use the gamified environment for refining their existing requirements..

Introduction

Customers are looking for solutions and benefits, forcing the manufacturer to give increasing attention to understand and answer their problems over the whole life cycle. Product-Service Systems (PSS) emerge as a result through the integrated development, realization and application of tangible and intangible components for a common objective. Additionally, new levels of human-machine interaction have become possible and more widespread, paving the way for reliable, sustainable, technology-driven ecosystems [START_REF] Follett | Designing for Emerging Technologies: UX for Genomics, Robotics, and the Internet of Things[END_REF]. As a result, Cyber-Physical Systems (CPS) integrate embedded systems, application systems, and infrastructure in complex networks [START_REF] Baheti | Cyber-physical Systems[END_REF]. They follow a holistic system approach, requiring the collaboration of different disciplines such as mechanical engineering, electrical engineering, and computer science for their realization [START_REF] Follett | Designing for Emerging Technologies: UX for Genomics, Robotics, and the Internet of Things[END_REF]. The collaboration with stakeholders from different disciplines as partners during Requirements Engineering (RE) becomes more and more important. The high number of components involved in the system and its evolution along the life cycle require the RE approach to adapt to a volatile set of user requirements, evolving over the life cycle as the technical development continues and the needs of the different customers and stakeholders change over time.

Consequently, for CPS based PSS the need for continuous interaction between the development process and the requirement elicitation process is inevitable for ensuring a consistent and traceable elicitation and management of requirements [START_REF] Hull | Requirements Engineering[END_REF]. This requires new elicitation approaches and tools, being more flexible, dynamic and considering future needs even before they have appeared, in order to reduce the costs and the quality challenges arising from this dynamic environment, i.e. there is a need for a collaborative approach of all stakeholders involved in the entire product life cycle. This article present the first results of a gamified approach for the requirements elicitation for CPS based PSS that can be applied in such dynamic environments. The work is based on a RE framework that enables a symbiotic specification of dynamic systems in a collaborative way along the whole value chain.

Methodology

For the development of the gamified approach, we combine literature review and action research. In a first step, the relevant characteristics of CPS based PSS and the RE process are identified. Secondly, several existing approaches that might serve as a good basis for the gamification will be assessed for their suitability. The main assessment criteria are to what extent the existing approaches and methodologies are transferable to CPS based PSS, as well as to what extent it appears likely that their re-use or adaption will contribute to improved quality of requirements elicitation. Thirdly, based upon this analysis, existing gamification approaches can be further developed or changed in order to address these points.

For the literature review, scientific papers were accessed through suitable portals (Scopus, Elsevier, Google Scholar etc.) searching for key words (serious games + requirement elicitation, product-service systems, cyber-physical systems, Requirements Engineering, dynamic systems) [START_REF] Kitchenham | Systematic Reviews in Software Engineering-a Systematic Literature Review[END_REF]. The relevance of the identified papers for this article was based on assessing the abstract, as well as by searching for the combination of elicitation, PSS and CPS in the full papers, considered being the most challenging, and that there is a need of tools supporting the process.

The work with four industrial use cases had a different methodical approach. The researchers have been involved in the specifications and development of the CPS/PSS scenarios. Design Science was the overall scientific approach in this work. More specific, action research was applied. The game has been developed using an agile software development approach.

Requirements Engineering Approaches for CPS based PSS

From the PSS definitions, the main components to be covered in an integrated approach are tangible product and intangible service shares jointly fulfilling a user's need [START_REF] Baines | others: State-of-the-art in Productservice Systems[END_REF][START_REF] Goedkoop | others: Product Service Systems, Ecological and Economic Basics. Report for Dutch Ministries of environment[END_REF]. Additionally, IT components, such as software, are becoming more and more a distinct part of PSS [START_REF] Meier | Industrial Product-service Systems-IPS 2[END_REF], ultimately leading to the provision of services through CPS [START_REF] Geisberger | Integrierte Forschungsagenda Cyber-Physical Systems[END_REF]. In order to derive the challenges for requirements elicitation for CPS based PSS, the specific characteristics of the separate components and their development processes are described below.

For product development, RE approaches have already been implemented with a high degree of formalization. Structured fundamental models exist that provide a general development procedure including RE. However, they focus almost exclusively on requirements development as the main process, which is only conducted at the beginning of the development approach, e.g. by specifying the product requirements document [START_REF] Pahl | Konstruktionslehre: Grundlagen Erfolgreicher Produktentwicklung; Methoden und Anwendung[END_REF]. Sometimes, also aspects of requirements management are adopted, but without explicit instructions for implementation [START_REF] Husen | Anforderungsanalyse für Produktbegleitende Dienstleistungen[END_REF]. For requirements elicitation, first, the stakeholders are identified; however, procedures for the elicitation of requirements for product-related services are not described. Moreover, there are weaknesses in the derivation of requirements from the customer's value chain processes, and cross-domain knowledge is not considered [START_REF] Berkovich | Requirements Engineering für Product Service Systems[END_REF].

Models for the systematic development of services have been created [START_REF] Bullinger | Service Engineering-Entwicklung und Gestaltung Innovativer Dienstleistungen[END_REF]. However, no systematic procedures for the implementation of RE have been established, because the characteristics of a service, e.g. its complexity, pose greater challenges. Thus, service engineering procedures do not integrate a holistic RE until now, but focus more on methods like "trial and error" [START_REF] Spath | Entwicklung hybrider Produkte-Gestaltung Materieller und Immaterieller Leistungsbündel[END_REF]. The elicitation process in service engineering comprises the tasks of identifying essential information -e.g. service ideas, possible customers and their expectations, and the sources of the requirements -and determining the goals, chances and risks. The procedures are service-domain specific; cross-domain knowledge is not considered. Furthermore, no precise methods for the elicitation are provided. Procedures for the requirements elicitation are described on a relatively general level [START_REF] Husen | Anforderungsanalyse für Produktbegleitende Dienstleistungen[END_REF].

In the IT sector, RE is widely recognized as a special discipline; RE "has begun to evolve from its traditional role, as a mere front-end in the software development lifecycle, towards becoming a key focus in the software development process" [START_REF] Aurum | Engineering and Managing Software Requirements[END_REF]. In direct comparison with product and service development, RE is integrated deeper and more comprehensive into software development [START_REF] Husen | Anforderungsanalyse für Produktbegleitende Dienstleistungen[END_REF]. Customer-integration is emphasized in the software engineering approaches, but the focus is laid upon the software domain -interdisciplinary requirements are not considered. The procedures provided for the identification of conflicts focuses solely on the software domain; interdisciplinary conflicts are not discovered. Negotiation with stakeholders is suggested to resolve conflicts and find a compromise [START_REF] Berkovich | Requirements Engineering für Product Service Systems[END_REF].

Gap Analysis

According to [START_REF] Berkovich | Requirements Engineering für Product Service Systems[END_REF], the literature about PSS development and design discusses the process of development only abstractly without going into detail. Firstly, the "organizational conditions are created in order to enable an integrated development of services and hardware/software". The stakeholder needs -regarding products and services -are identified. Concrete techniques or methods are not mentioned. Current RE approaches are not able to handle the large number of different and conflicting requirements without exponentially increasing time and cost, as contradictions and interdependencies have to be assessed for a large number of requirements in various domains [START_REF] Jarke | The Brave New World of Design Requirements[END_REF].

Based on this gap analysis, requirements elicitation for CPS based PSS has to be formal enough to describe the targeted system unambiguously and in a verifiable way, but has to have the flexibility to include non-formal inputs. The different stakeholder needs and changing requirements must be managed. As the functionalities of a PSS emerge from the cumulative interactions of the product, service and IT components, elicitation methods and tools have to be able to integrate the mechanical, service and IT domain for capturing requirements. These requirements have to be mapped subsequently to the different PSS elements, to be either fulfilled by a physical functionality or a cyber-service execution. Berkovich et al. [START_REF] Berkovich | A Requirements Data Model for Product Service Systems[END_REF] propose to apply the Domain-Mapping-Matrix (DMM) to relate the requirements with the PSS functions. This implies communication between stakeholders from different disciplines and that the following aspects have to be observed:

-Complexity: Elicitation has to be able to handle a large number of interrelated product, service and IT requirements. -Distributed stakeholders: Elicitation has to be applicable for a large number of stakeholders that are typically separated spatially and organizationally. This involves the user, who defines the scope and purpose of the PSS, as well as specialized partners with distinct processes, which develop the individual system components. -Different disciplines: The elicitation approach has to be usable in multiple disciplines. Requirements exchange has to be supported in order to create a common view of the targeted system

The following sections will describe how a gamified approach could support requirements elicitation to fulfill the preconditions above.

Gamification

A gamification of RE activities does not imply turning PSS development into a game. It means using game-based elements and mechanisms in this non-game environment with the purpose of employing the motivational properties of games [START_REF] Wood | Gamification[END_REF]. Thus, the gamification components and elements need to be designed and adapted to the context of RE for cyber-physical Product-Service Systems. To do so, it is necessary to establish clear goals and rewards, mechanisms of progression, intermediary and final statuses, challenges, as well as avoiding to manipulate users into following certain patterns that are unlikely to take otherwise, relying too much on extrinsic motivational factors [START_REF] Kapp | The Gamification of Learning and Instruction Fieldbook: Ideas Into Practice[END_REF].

The objective of a gamified requirements elicitation would be to make the work routine of need identification more effective. The outcome of the game could be initial ideas, but also imply "options", e.g. solutions for specific problems. One advantage of this approach compared to other current techniques is the motivating aspect, which could reduce the frustration in an idea generation process. The game can easily contain multiple and contradictory knowledge structures and promote discussion and reframing of ideas. At the same time, gamification provides incentives to change existing culture, routines and behaviour. Additionally, the game can develop explicit routines for team-based ideation work, together with a technological infrastructure that allows for communication about, and experimentation with more or less finished ideas, early stage innovations and concepts not yet implemented. The objective for the elicitation process would therefore be to play with different options in a virtual environment for discovering the limitation of the defined requirements as well as to use the virtual environment to support the ideation of new possible services. The final criteria for why incorporating gamification in elicitation is the possibility to provide the user with immediate feedback on how the decision or a change in a variable will influence the system configuration for validation.

We decided to use "Unity" as game engine [19], so that the player can get an individually adapted end user scenario without having the need of reprogramming. The game is as much as possible adapted to the known business environment of the industrial cases, with a direct and participatory involvement of stakeholders. Based on these considerations, the gamified environment needs to:

-Involve all stakeholders independent from location or organization, which could be done using internet-based games. -Mirror the working environment for each role sufficiently, which requires an analysis of each stakeholders work processes. -Support the users possibility to contribute to a disruptive innovation, e.g. by providing support for out-of-the-box thinking without limiting ideas. -Visualize the consequences of the defined requirement, e.g. for other requirements and the resulting solution.

The above-mentioned boundaries lead to the following consideration on how to prepare a gamified environment. In the engine, we mapped the existing to-be scenarios and the preliminary user requirements. These requirements are included as functions, where the player can change the variables. We use narrative story telling for leading the player through the game play. It is facilitated and the roles are similar to those in their own companies.

Use Case

The gamification approach has been successfully applied in three industrial PSS use cases and is currently being prepared for an additional cyber-physical Product-Service System scenario. The company is a vendor for the aviation sector, which offers fully integrated solutions for surveillance systems, certified according to aviation standards. Customers are airlines, which retrofit their aircraft with the buyer furnished surveillance solutions from the vendor. It generates video streams, which are stored on a memory cartridge within the Central Video Unit (CVU/DVR). The idea is to use this product and extend it with different services. The scenario is depicted in Fig. 1 below. Based on a to-be analysis and a first specification of the end user needs, the following restrictions for service development have been identified:

-The product in the aircraft (CVU/DVR) must not be modified.

-The product outside of the aircraft -as for instance the Ground Station (where the data are viewed) -can be modified. For the service-based Aircraft Surveillance System modifications of the hardware (e.g. internal hard drive to copy the data to) as well as software are required. -In addition, processes within the company has to be re-viewed and reorganized, thus resulting in several as well as radical changes:

Thus, the requirements need to be defined for a fuzzy area, since it is expected that the service the aircraft vendor would like to offer will be customized and in addition, since nothing similar exists, be adaptable to still uncovered needs. The game play starts with a screen that allows the players to enter their name and role (e.g. production, sales etc.) according to their position in the company. Through storytelling, they get the task to develop a cyber-physical Product-Service System, e.g. for an airline that wants a specific service. The players are then able to specify requirements for support in this process from the perspective of their role. They have the possibility to look into an existing repository for similar already existing ideas and requirements or write their own. The different players look at the challenge from different perspectives and provide ideas for the other roles' requirements. The results are then displayed by the game and can be rated by all players. Based on the ratings, the players discuss the best ideas to create an integrated solution. This ends the game and it can be restarted iteratively to discuss more requirements and ideas.

The game scenario has been implemented as described above. Additional game mechanics related to KPIs (costs, time, quality, and possible market price), interaction and collaboration could be added. Letting the player first play around with the system and the data that can be collected will make him aware of the CPS environment and its limitations. Furthermore, in order to foster the creativity and to think out of the box, different events may trigger the game play in future releases, and the players are obliged to use tools (like a modelling tool for products or services) in the phase where they are normally not usede.g. in the test phase. The idea is here to support the critical thinking and to let the player verify that the tool is flexible enough to react on future needs.

Conclusion

This paper first outlines the challenges that are related to the requirements elicitation process of CPS based PSS. It discusses the challenges that arise from the fact that the requirements for such complex systems being applied in a dynamic environment need to involve distributed stakeholders from different disciplines. The second part of the article presents a gamified approach for PSS. The approach has been applied in three industrial use cases with good results.

It is able to meet the needs defined in section 5, with regards to the gaps identified in section 4. Gamification is able to involve all stakeholders in a servitization scenario. While the approach currently only includes company roles, it is no problem to extend it to third party suppliers, service providers and the customer. As it is playable over the internet, also distributed partners can be involved. The role model also allows the game to sufficiently mimic the working environment of the players from different disciplines by simulating specific tools, office spaces and work processes. Disruptive innovation is supported by giving the player the freedom to enter ideas independently from existing solutions and share them beyond domain borders. Finally, the ideas are discussed collaboratively by all stakeholders, thus taking into account their needs to define a suitable solutions despite the inherent complexity.

Future research and development needs to strengthen simulation as game component, to give the players a more realistic environment and prediction of results. This would strengthen the feedback to the players and contribute to more dynamic and detailed requirements as an outcome.

Fig. 1 .

 1 Fig. 1. Cabin Video Surveillance System (CVSS) scenario

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.


Kiwook Jung
email: kiwook.jung@nist.gov

Boonserm Kulvatunyou

Sangsu Choi

Michael P Brundage

An Overview of a Smart Manufacturing System Readiness Assessment

Keywords: Smart manufacturing readiness, Smart factory, Maturity model

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

Introduction

Manufacturers lack a concrete methodology to choose and prioritize emerging technologies that aid in the creation of smart manufacturing systems and factories. On top of this, manufacturers may need to implement organizational and process improvements to realize the full benefits from these technologies. A survey indicate that most manufacturers have trouble making such improvements [START_REF]Manufacture Innovation[END_REF]. While larger companies can bring in consultants to assist with such issues, small and medium size manufacturers typically do not have the funds to do the same. Existing methods such as the Supply Chain Readiness Level [START_REF]Manufacture Innovation[END_REF] and MESA Manufacturing Transformation Strategy [START_REF] Mesa | Transforming Manufacturing Maturity with ISA-95 Methods[END_REF] exist, but they largely ignore the use of information and communication technologies (ICT) as a primary foundation for making those improvements. There are existing works, which study the impact of Information Technology (IT) adoption to businesses (also known as business & IT alignment). However, each study typically focuses on evaluating a single technology such as the Enterprise Resource Planning (ERP) system or Manufacturing Execution System (MES). These studies have not taken into account other aspects of the organization that can affect the impact of the respective technology adoption. This paper describes our initial work to develop a method for assessing a factory's readiness for incorporate emerging ICT technologies to become a smart factory. In our view, a smart factory uses ICT to maintain and improve its operational performance in response to its changing environment. Consequently, the method breaks down the assessment into four maturity components including the IT, the information connectivity, organization, performance management program maturities. Our method then combines these assessments into a single Smart Manufacturing System Readiness Level (SMSRL) index, which can be used for benchmarking individual factories or as criteria for selecting a supplier among several factories. In addition to describing our method, we discuss a correlation analysis that we performed. That analysis shows that the SMSRL index has a positive correlation with the operational performance.

Next we discuss related work in more detail before describing the SMSRL assessment method. Then, the result from the validation study is presented and a conclusion and remarks are given.

Related Work

Several types of readiness levels are used within the manufacturing sector. Technology Readiness Level (TRL) indicates the maturity of a technology for commercial adoption [START_REF] Mankins | Technology readiness levels[END_REF]. Similarly, Manufacturing Readiness Level (MRL) indicates the maturity of a manufacturing process technology [START_REF] Wheeler | Manufacturing Readiness Assessment for Fuel Cell Stacks and Systems for The Back-Up Power and Material Handling Equipment Emerging Markets[END_REF]. An organization can use the same scale to indicate the maturity/capability of its respective technology as well. These methods do not evaluate a particular company for its readiness to adopt a particular technology. Supply Chain Readiness Level (SCRL) [START_REF]Manufacture Innovation[END_REF] provides a method to assess the ability of the supply chain to operate and to achieve specific operational performance targets. The readiness levels are associated with characteristics within fifteen (15) categories that discretely provide an improvement roadmap for a supply chain design and the operation. Similar to the TRL and MRL, SCRL does not provide a methodology for a particular organization to assess its readiness to adopt a particular technology, which may correspond to some categories of the characteristics.

The MESA manufacturing transformation strategy (MTS) provides a framework based on the ISA-95 standard [START_REF] Mesa | Transforming Manufacturing Maturity with ISA-95 Methods[END_REF] to prepare an organization for Manufacturing-Operation Management (MOM) technologies adoption in four (4) business domains including Business Processes, Organization Structure, Personnel Skill Sets, and Manufacturing System Technology.

The SMSRL assessment objective is similar to that of the MESA-MTS albeit with the scope going beyond MOM technologies. Technically, the SMSRL index provides an indication of the current state with respect to a reference model. Both the SMSRL and the MESA-MTS allow the reference model to evolve as new technologies emerge and become available. Because of this, the assessment piece of the method, by design, is kept independent of the reference model.

Method

Erro! Fonte de referência não encontrada. provides an overall architecture of the readiness level assessment. It summarizes the steps, the inputs, and the outputs involved in the assessment followed by improvement plan development. The process is iterated after the plan has been implemented. The primary purpose of the proposed assessment based on the SMSRL index is to 1) help manufacturers determine their current level and 2) develop a customized improvement plan.

Fig. 1. Overall assessment framework

Profiling the Current State

The SMSRL proposed in this paper is based on the Factory Design and Improvement (FDI) reference-activity model defined in [START_REF] Jung | An Activity Model for Smart Factory Design and Improvement[END_REF]. That model provides a set of reference activities; information entities for input, output, and constraints on each activity; and relevant software functions using the IDEF0 functional requirement modeling method [7]. On the basis of this model, we developed a questionnaire for profiling [START_REF] Jung | Reference Activity Model-based Factory Design and Operations Evaluation Framework[END_REF]. It is to be answered by relevant factory personnel. The questionnaire is organized into four measurement dimensions (C1 to C4) each of which consists of measurement items (process, designated personnel, etc.) as shown in Erro! Fonte de referência não encontrada.. See the citations in Erro! Fonte de referência não encontrada. for the sources of these dimensions. Next we discuss each dimension in more detail.

Fig. 2. SMSRL measurements

The Organizational maturity dimension (C1) is conceptually defined as the comprehensiveness of the activities in the reference activity model performed by the manufacturers. It is measured by 1) whether there is a process that formally manages each activity; and 2) whether there is a responsible human resource assigned to the activities.

The IT maturity dimension (C2) is conceptually defined as the degree to which IT resources are available and working. The IT resources refer to computerized tools and methods. For example, a paper-based analysis method for layout design would not be qualified as an IT resource.

The Performance Management maturity dimension (C3) is conceptually defined as the degree to which the performance measures are used and monitored. This dimension also takes into account the connectivity between different operational performance measures where appropriate.

Lastly, the Information connectivity maturity dimension (C4) is conceptually defined as the maturity of the method to exchange the required information and the degree to which the information is shared/exchanged.

Profiling the current state consists of three operations: scope determination, information collection and consolidation. The scope is represented by relevant activities and stakeholders. The FDI model also indicates stakeholders relevant to each activity based on the ISA-88 manufacturing control architecture [9]. Information collection and consolidation are performed collaboratively among the group of stakeholders that are relevant to the scope.

Evaluate Current State

The evaluation of the current state compares the profile to the reference activity model. Computation methods, as shown in Erro! Fonte de referência não encontrada., are applied to each measurement dimension resulting in quantitative measures that can be used for comparison and benchmark. The counting measure is the ratio between the number of elements employed in the current practice and those suggested in the reference activity model. For example, the number of software functions (per the reference model) available in the factory divided by the number of all the software functions identified in the reference model gives a C2 measure.

Table 1. Computation Methods for SMSRL

SMSRL Construct

Computation Method C1: Organizational maturity [START_REF] Raymond | Measurement of Information Technology Sophistication in Small Manufacturing Businesses[END_REF] Counting measure, Activity maturity scoring scheme C2: IT maturity [START_REF] Raymond | Measurement of Information Technology Sophistication in Small Manufacturing Businesses[END_REF] Counting measure C3: Performance management maturity [START_REF] Maasouman | Development of A Lean Maturity Model for Operational Level Planning[END_REF] Counting measure C4: Information connectivity maturity [START_REF] Chung | The Impact of Information Technology Infrastructure Flexibility On Strategic Alignment and Application Implementations[END_REF] Incidence matrix-based similarity measure, Incidence scoring scheme

The Activity maturity scoring scheme is based on the Capability Maturity Model Integration (CMMI) [START_REF]CMMI for Development[END_REF]. The stakeholder of each activity scores the maturity of the activity based on the scale shown in Erro! Fonte de referência não encontrada..

The incidence matrix is commonly used to represent and analyze interactions between entities in a complex system. Here, an incidence matrix is used to represent the information entities connected between activities; and as such can be used to quantify the information connectivity maturity (C4). It is an n x n matrix where n is the number of activities under evaluation, the row is the activity that provides the information entity (from-activity or sender activity), and the column is the activity taking the information entity as an input (to-activity or receiver activity). The cell, the incidence, indicates the maturity of the information flow from the row to the column. Erro! Fonte de referência não encontrada. shows a schematic view of an incidence matrix. The maturity of the information flow is marked by the scoring scheme shown in Erro! Fonte de referência não encontrada. with the highest score (1) being connected by a standard data exchange. All reference incidence matrices assume the highest score where there is the information connectivity between the from-and to-activity. A score of 0.7 represents that software capability for data exchange among activities exists, but information is not currently exchanged. When the data is exchanged manually between activities, the score is 0.3. A score of zero indicates that there is no data exchange between the activities. Manual transformation required from output data a to compatible data formats for software system m

0 if Ref = 0 then, c = 0xRef No exchange required 0 If i 𝑜𝑟 𝑗 = ∅ then, c = 0xRef
The current state does not perform the activity i or j. to be performed

0 If i=j then, c = 0xRef

Recursive

Where i is the sender activity; a is the output data format of the activity i; Sj is a set of standard data formats associated with the receiver activity j; Bm is a set of compatible data formats for the receiver software system m; and c is the incidence score.

The evaluation result can be visualized as shown in Erro! Fonte de referência não encontrada.. Each indicator can be used individually or combined into a single SMSRL index. For simplicity, a single SMSRL index was computed using an average of C1, C2, C3 and C4. The overall index and/or individual construct can be used to prioritize the factory improvements or to evaluate potential suppliers.

Fig. 3. An exemplary assessment result

Develop Improvement Plan

In the last step, the evaluation result is used to develop and prioritize an improvement plan. A classification analysis shown in the next section provides a high-level improvement recommendation. Our future work lies in developing a method to provide a more detailed recommendation.

Validation Study

This section investigates the validity of the proposed assessment using a similar approach to [START_REF] Chung | The Impact of Information Technology Infrastructure Flexibility On Strategic Alignment and Application Implementations[END_REF]. First, data about the relationships between the SMSRL and operational performance was collected. Then, hypothesis tests for the statistical significance of the relationships were performed. Lastly, we analyzed patterns of the SMSRL that can guide an improvement plan development. These activities are explained below. Data Used for the Validation. Existing studies in the domain of business and IT alignment were used for the validation. A detailed analysis on the existing studies can be found in [START_REF] Jung | Reference Activity Model-based Factory Design and Operations Evaluation Framework[END_REF]. Different alignment constructs (i.e., measurement items) from these studies were mapped to performance categories (e.g., operational, financial) and were statistically correlated using empirical data.

Validation Method. To establish the relationship between the SMSRL assessment and the performance categories, the measurement items of the SMSRL assessment are mapped to those considered in the studies (operational, financial, value-based, and overall). A similarity value between the SMSRL assessment and the target study is then calculated using the n-gram measure (intersection divided by union). This gives the basis for the correlation analysis shown in the next subsection.

Hypothesis Test. Four hypothesis tests were performed. Statistically significant, positive-correlations with the SMSRL index were found on the operational performance, overall performance, and value-based performance as shown in Erro! Fonte de referência não encontrada.. The financial performance was not found (hence not shown) to have a statistically significant positive-correlation.

Table 5. Hypothesis test results

Hypothesis p-value Sig

H1: the higher the similarity value, the higher the operational performance attributable to alignment 0.713 Yes (p < 0.05) H2: the higher the similarity value, the higher the overall performance attributable to alignment 0.404 Yes (p < 0.05) H3: the higher the similarity value, the higher the value-based performance attributable to alignment 0.529 Yes (p<0.05) High-level Recommendation. A k-means-clustering analysis on the simulated SMSRL results has been performed (k=3). Based on its result shown in Erro! Fonte de referência não encontrada., a high-level recommendation can be made for each SMSRL cluster. The cells with bold-font values show the category of improvement a factory should focus on to have the largest impact on a respective performance category. For example, the first row indicates that improvements in the information connectivity (C4) is likely to have the best impact on the operational performance.

Conclusion and Remark

We introduced a new, smart manufacturing system readiness assessment (SMSRL). SMSRL measures the readiness using maturity scoring of four dimensions: Organizational, IT, Performance management, and Information connectivity maturities. The core of the smart manufacturing concept is the ability to use information effectively. The SMSRL assessment provides a quantitative measure of this ability. Such measure, which is in the form of an index, can be used for benchmarking. The statistical analysis shows that the index has a positive correlation with three types of performance: operational, overall, and value-based.

The SMSRL index provides a real number as its readiness measure. The SCRL, on the other hand, provides discrete readiness levels. Each type of measure has its advantages. Discrete measures lend themselves readily to definitional levels. Real-numbered levels do not; however, they can be used in other quantitative analysissuch as the ones shown in section 4. Discrete measures cannot

In our future work, we will 1) develop a method to provide more detailed improvement recommendations 2) extending and/or experimenting with other models used as a reference for the assessment.

Table 2 .

 2 Activity maturing scoring scale

	Linguistic scale	Task score	Characteristics
	Not performed	0	-
	Initial	1	Processes established, but unpredictable
	Managed	3	Processes characterized for projects
	Defined	5	Process characterized for the organization
	Qualitative	7	Processes measured and controlled
	Optimizing	9	Focus process improvement

Table 3 .

 3 Activity incidence matrix

	From/To	To Act1	…	To Actj
	From Act1	inc11	…	inc1j
	…	…	…	…
	From Acti	inci1	…	incij

Table 4 .

 4 Incidence scoring scheme

	Score	Scoring Rule	Definition
	1	if a∈(Sj∩Bm) then, c = 1xRef	Standard data formats for activity j (and) compatible data formats for software system m
	0.7	c = 0.7xRef if a∈Bm then,	Compatible data formats for software system m
	0.3	if a∉Bm then, c = 0.3xRef

Table 6 . High-level recommendation SMSRL Centroid (mean score) Performance Category Standardized Coefficient of Independent Variables

 6

	C1	C2	C3	C4


Eiji Morinaga
email: morinaga@mapse.eng.osaka-u.ac.jp

Nattapoom Charoenlarpkul
email: c.nattapoom@mapse.eng.osaka-u.ac.jp

Hidefumi Wakamatsu
email: wakamatu@mapse.eng.osaka-u.ac.jp

Eiji Arai
email: arai@mapse.eng.osaka-u.ac.jp

An Improved Computer-Aided Process Planning Method Considering Production Scheduling

Process planning is essential for achieving a sophisticated manufacturing system, and computer-aided process planning (CAPP) have been discussed. Considering recent requirements for realizing agile manufacturing, a set of flexible CAPP methods have been developed, in which process planning for one product using one machine is dealt with. In actual manufacturing, multiple workpieces are usually machined with multiple machine tools in the same period, and pursuing optimality for each product independently may result in poor productivity. For this reason, integration of process planning and production scheduling was performed by formulating the integrated problem as a 0-1 integer programming problem. However, this formulation involves huge computational load. This paper provides an improved method where the integrated problem is formulated as a mixed integer programming problem.

Introduction

In order to convert product design data into a real product, it is necessary to perform process planning, that is, to select manufacturing processes and determine the sequence in which they are carried out. Because it plays an important role as a bridge between product design and manufacturing, numerous works on computer-aided process planning (CAPP) have been actively conducted [START_REF] Isnaini | Review of Computer-Aided Process Planning Systems for Machining Operation -Future Development of a Computer-Aided Process Planning System[END_REF].

Recent diversified and changeable customers' needs have increased a need to realize agile manufacturing [2] that is capable of immediately adapting to changes in the manufacturing situation, and flexibility has been a keyword in recent manufacturing. This need is also being addressed in research related to CAPP [3]. This research aimed at developing autonomous machine tools that require no NC programming and can flexibly adapt to changes in the manufacturing situation, and a flexible process planning method for rough milling was proposed. This method consists of four main steps-(i) decomposing the total removal volume (TRV) through the application of decomposition rules to transform it into sets of machining primitive shapes (MPSs), (ii) converting each of the MPS sets to a set of machining features (MFs) by determining a machining sequence for each set of MPSs and recognizing each MPS as an MF, (iii) executing rough operation planning by applying a tool selection rule and a case-based reasoning system for cutting condition decisions, and (iv) extracting the optimal set of MFs to achieve the shortest machining time with information on the machining sequence and the utilized tools as the optimal process plan. With this method, process plans are generated and then the optimal plan is selected. Therefore, when the manufacturing situation changes, it is possible to quickly provide a new optimal plan by executing steps (iii) and (iv). Several enhancements have been made to this method for enabling extraction of a better set of MFs [4], for taking multi-axis milling into account and reducing computational complexity [5], and for improving computational efficiency [6].

These methods deal with process planning to create one product using one milling machine. In actual manufacturing, multiple workpieces are usually machined with multiple machine tools in the same period, and pursuing the optimal plan without consideration of total production may result in poor productivity. Considering this point, selection of the optimal process plan in the flexible CAPP methods and production scheduling (PS) were integrated, and selection of a set of the optimal process plans for multiple workpieces from the point of view of total productivity was formulated as a 0-1 integer programming problem [7]. However, this formulation needs a huge number of 0-1 variables, since it is necessary to define the variables for each sub-period defined by dividing the whole period, and therefore this method involves large computational load.

In this paper, this method is improved by formulating the integrated problem as a mixed integer programming (MIP) problem. In the next section, the flexible CAPP method [6] is outlined, and then the problem of the conventional integrated method [7] based on this CAPP method is explained. Section 3 provides formulation of the integrated problem of selection of the optimal process plans for multiple products and PS as an MIP problem. This improved method is applied to an example in Section 4, and Section 5 presents our conclusion.

Overview of Conventional Method

This section provides an outline of the conventional CAPP method [5,6], which was improved considering integration with PS [7] and will be also improved further in Section 3. In this method, which is for rough milling, it is assumed all surfaces of the workpiece and the product are parallel to the xy, yz or zx plane of an orthogonal coordinate system and the tool approaches the workpiece along one of these axes (Fig. 1). Process planning is performed by the following steps:

TRV extraction

The total removal volume (TRV), which is the volume to be eliminated from a workpiece to obtain the product shape, is calculated by subtracting the product shape from the workpiece shape (Fig. 2).

Concavity-based division

A cutting plane is generated at a concave part of the TRV contour by extending a surface, and then the TRV is divided by it. This process is repeated until the division has been executed at all concave parts, and the TRV is converted into a set of machining primitive shapes (MPSs). Since type of the MPS set depends on the generation direction and sequence of the cutting planes, multiple MPS sets can be produced from one TRV (Fig. 3).

Machining sequence and direction assignment

For each MPS set, the machining direction (Fig. 1) for each MPS and the machining sequence for those MPSs are considered.

MF recognition

The machining directions and sequence assignment enables recognizing an MPS as a machining feature (MF) based on the number of its "open faces" and the relationship among its vertices and edges. For each MPS set, multiple MF sets are generated depending on the direction and sequence (Fig. 4).

Process plan generation

For each MF set, a tool used for each MF is chosen from available tools by applying a given rule, and the machining condition for the MF is decided by a case-based reasoning system [8]. This operation generates, for each MPS set, MF sets including information about the machining sequence, the machining directions, and the tools to be used-that is, a process plans is generated.

Evaluation

For each process plan of each MPS set, the total machining time is estimated. The plan that achieves the shortest total machining time is selected as the optimal process plan for the MPS set by the full search [5] or mathematical optimization framework [6]. After performing this operation for all MPS sets, the estimated total machining times for the optimal plans are compared with each other. The optimal plan for which the estimated total machining time is the shortest is ultimately output as the optimal process plan for the TRV.

In actual manufacturing, multiple workpieces are usually machined by using multiple machines in the same period. If this method is applied to those workpieces, the optimal plan is generated for each of them independently. Those plans would not be optimal from the point of view of manufacturing systems, since a machine tool can machine only one workpiece at a time. It is desirable to integrate process planning by this method with PS, and the integrated problem was formulated as a 0-1 integer programming problem where 0-1 variables are defined for each sub-period defined by dividing the whole period [7]. Since machining requires long time generally, the number of those variables are huge and therefore the integrated method involves a very large computational load.

Improved Integrated Method of CAPP and PS

This section provides formulation of the integrated problem of the optimal plan selection and PS as an MIP. Two kinds of 0-1 variables x avS1•••SN dt , y a,i,b,j and three kinds of real variables s m a,i , f m a,i , C max are introduced, where a, b ∈ R := {1, . . . , R} and v ∈ V := {1, . . . V } stand for the ID number of product and its MPS set, respectively, and N is the total number of the MPSs. (It is assumed that the total numbers of MPS sets and MPSs in the set are same for any product and any MPS set.) S k is the ID number of the MPS that is machined after machining other k -1 MPSs. S 1 takes a value in N := {1, . . . , N }, and S k , k ≥ 2 takes a value in {0} ∪ N , k ≥ 2. S k = 0, ∀ k > k means only the

x avS1•••S k-1 S k 0•••0dt = 1 means
that the MPS S k of the MPS set v for the product a is machined in the direction d with the tool t after machining MPS S 1 , S 2 , . . . , S k-1 in this order, and the time required for this machining is

P avS1•••S k-1 S k 0•••0dt
, which has been calculated in advance and set to an negative value for unfeasible machining. y a,i,b,j = 1 means the i-th operation of product a is executed after the j-th operation of product b. s m a,i and f m a,i stand for the starting and finishing times of the i-th operation of product a. C max is the time at which all operations are completed. Let τ m a,i is the required time for the i-th operation of product a by machine m, T m is the set of tools implemented on machine m and M is a positive value that is large enough, then the problem of finding the optimal plans for the products which achieve the smallest makespan C max is described as an MIP by the following equations and inequalities. (1-(12)) are same as those in the conventional method, (14-( 20)) are for formulation of PS problem as an MIP, and equation ( 13) integrates CAPP and PS. minimize: C max (1) subject to:

P avS1•••Si0•••0dt • x avS1•••Si0•••0dt ≥ 0, ∀a ∈ R, ∀v ∈ V, ∀S 1 , . . . , S i ∈ N , i ∈ N , d ∈ D, ∀t ∈ T (2) V ∑ v=1 N ∑ S1=1 6 ∑ d=1 T ∑ t=1 x avS10•••0dt = 1, ∀a ∈ R (3) . . . V ∑ v=1 N ∑ S N =1 S N ̸ =S N -1 ,•••S1 • • • N ∑ S2=1 S2̸ =S1 N ∑ S1=1 6 ∑ d=1 T ∑ t=1 x avS1S2•••SN dt = 1, ∀a ∈ R (4) V ∑ v=1 N ∑ S1=1 6 ∑ d=1 T ∑ t=1 x avS10•••0dt ≤ 1, ∀a ∈ R (5) . . . V ∑ v=1 N ∑ SN =1 • • • N ∑ S2=1 N ∑ S1=1 6 ∑ d=1 T ∑ t=1 x avS1S2•••SN dt ≤ 1, ∀a ∈ R (6) 6 ∑ d=1 T ∑ t=1      x avS10•••0dt + N ∑ S k =1 • • • N ∑ S1=1 S1̸ =S1 x av S1•••Sk0•••0dt      ≤ 1, ∀k ∈ N \ {1}, ∀a ∈ R, ∀v ∈ V, ∀S 1 ∈ N (7) N ∑ S1=1 6 ∑ d=1 T ∑ t=1      x avS1S20•••0dt + N ∑ S k =1 • • • N ∑ S2=1 S2̸ =S2 x avS1 S2•••Sk0•••0dt      ≤ 1, ∀k ∈ N \ {1, 2}, ∀a ∈ R, ∀v ∈ V, ∀S 2 ∈ N (8) . . . N ∑ S N -2 =1 • • • N ∑ S1=1 6 ∑ d=1 T ∑ t=1      x avS1•••S N -1 0dt + N ∑ S N =1 N ∑ SN-1=1 SN-1 ̸ =S N -1 x avS1••• SN-1SN dt      ≤ 1, ∀a ∈ R, ∀v ∈ V, ∀S N -1 ∈ N (9) N ∑ S1=1 6 ∑ d=1 T ∑ t=1   xavS 1 0•••0dt + V ∑ ṽ=1 ṽ̸ =v N ∑ S2=1 x aṽS1S20•••0dt    ≤ 1, ∀a ∈ R, ∀v ∈ V (10) N ∑ S1=1 6 ∑ d=1 T ∑ t=1   xavS 1 0•••0dt + V ∑ ṽ=1 ṽ̸ =v N ∑ S3=1 N ∑ S2=1 x aṽS1S2S30•••0dt    ≤ 1, ∀a ∈ R, ∀v ∈ V (11) . . . N ∑ S1=1 6 ∑ d=1 T ∑ t=1   xavS 1 0•••0dt + V ∑ ṽ=1 ṽ̸ =v N ∑ SN =1 • • • N ∑ S2=1 x aṽS1S2•••S N dt    ≤ 1, ∀a ∈ R, ∀v ∈ V (12) τ m a,i = V ∑ v=1 N ∑ Si=1 • • • N ∑ S1=1 6 ∑ d=1 ∑ t∈Tm P avS1•••Si0•••0dt • x avS1•••Si0•••0dt , ∀a ∈ R, ∀i ∈ N , ∀m ∈ M (13) C max ≥ f m a,i , ∀a ∈ R, ∀m ∈ M, ∀i ∈ N (14) f m a,i = τ m a,i + s m a,i , ∀a ∈ R, ∀m ∈ M, ∀i ∈ N (15) s m a,i ≥ -1 • ( 1 - V ∑ v=1 N ∑ Si=1 • • • N ∑ S1=1 6 ∑ d=1 ∑ t∈Tm x avS1•••Si0•••0dt ) , ∀a ∈ R, ∀m ∈ M, ∀i ∈ N (16) s m a,i -M • V ∑ v=1 N ∑ Si=1 • • • N ∑ S1=1 6 ∑ d=1 ∑ t∈Tm x avS1•••Si0•••0dt ≤ -1, ∀a ∈ R, ∀m ∈ M, ∀i ∈ N (17) s m a,i+1 + M •   1 - V ∑ v=1 N ∑ Si+1=1 • • • N ∑ S1=1 6 ∑ d=1 ∑ t∈Tm x avS1•••Si+10•••0dt   > f m a,i , ∀a ∈ R, ∀m, m ∈ M, ∀i ∈ N \ {N } (18) s m a,i + M • ( 1 - V ∑ v=1 N ∑ Si=1 • • • N ∑ S1=1 6 ∑ d=1 ∑ t∈Tm x avS1•••Si0•••0dt ) ≥ f m b,j -M • y a,i,b,j -M •   1 - V ∑ v=1 N ∑ Sj =1 • • • N ∑ S1=1 6 ∑ d=1 ∑ t∈Tm x bvS1•••Sj 0•••0dt   , ∀a, b ∈ R, a ̸ = b, ∀m ∈ M, ∀i, j ∈ N ( 19
)
s m b,j + M •   1 - V ∑ v=1 N ∑ Sj =1 • • • N ∑ S1=1 6 ∑ d=1 ∑ t∈Tm x bvS1•••Sj 0•••0dt   ≥ f m a,i -M • (1 -y a,i,b,j ) -M • ( 1 - V ∑ v=1 N ∑ Si=1 • • • N ∑ S1=1 6 ∑ d=1 ∑ t∈Tm x avS1•••Si0•••0dt ) , ∀a, b ∈ R, a ̸ = b, ∀m ∈ M, ∀i, j ∈ N (20)

Case Study

The proposed method was applied to an example of R = 3, V = 4, N = 4, M = 2, T = 8, T 1 = T 2 = 4 (Fig. 5 and Table 1). The calculation was performed with a workstation (Intel Core i7-6700K 4.00GHz, 8GB RAM) and a commercial solver (IBM ILOG CPLEX Optimization Studio 12.6.2). The result shown in Table 2 and Figs. 6-7 was obtained after computing about 8 hours, though it was impossible to solve the problem by the conventional method.

Conclusion

The integrated method of flexible CAPP and PS has been improved by formulating the integrated problem as an MIP. It has become possible to obtain solutions for larger problems. Further improvement is still required for actual machining.

Fig. 1 .Fig. 2 .Fig. 3 .

 123 Fig. 1. Definition of machining directions. [7]

Fig. 4 .

 4 Fig. 4. MF recognition for an MPS set. Strings in each set stand for feature types ("CS", "OS", "OP", and "ST" stand for "closed slot", "open slot", "open pocket", and "step", respectively). [7]

Fig. 5 .

 5 Fig. 5. TRVs (the blue/brown/green volumes) and their dimensions (in mm).

Fig. 6 .

 6 Fig. 6. MPS set of the optimal plans. Fig. 7. Gantt chart.

Table 1 .

 1 Available

	Tool ID	1 2 3 4 5 6 7 8
	Tool Type	F F E E F F E E
	Diameter [mm]	3 8 4 6 4 7 5 9
	The number of teeth 4 4 4 4 4 4 4 4
	Machine ID	1 1 1 1 2 2 2 2

tools. "F" and "E" stand for facemill and endmill.

Table 2 .

 2 Machining Sanchez, L.M. and Nagi, R.: A Review of Agile Manufacturing Systems, Int. J. Prod. Res., 39,3561-3600 (2001) 3. Nakamoto, K., Shirase, K., et al.: Automatic Production Planning System to Achieve Flexible Direct Machining, JSME Int. J., Series C, 47, 136-143 (2004) 4. Hang, G., Koike, M., et al.: Flexible Process Planning System Considering Design Intentions and Disturbance in Production Process, Mechatronics for Safety, Security and Dependability in a New Era, 113-118, Elsevier (2007) 5. Morinaga, E., Yamada, M., et al.: Flexible Process Planning for Milling, Int. J. Auto. Tech., 5, 700-707 (2011) 6. Morinaga, E., Hara, T., et al.: Improvement of Computational Efficiency in Flexible Computer-Aided Process Planning, Int. J. Auto. Tech., 8, 396-405 (2011) 7. Morinaga, E., Joko, H., et al.: A Computer-Aided Process Planning Method Considering Production Scheduling, Advances in Production Management Systems: Innovative Management Towards Sustainable Growth, 348-355 (2015) 8. Nagano, T., Shirase, K., et al.: Expert System Based on Case-Based Reasoning to Select Cutting Conditions (in Japanese), J. JSPE, 67, 1485-1489 (2001)

	Product 1	2	3
	1st 4,3,2 3,6,2 3,3,8
	2nd 3,1,8 2,1,2 4,2,8
	3rd 1,5,2 1,1,8 2,1,8
	4th 2,5,2 4,2,8 1,1,8

sequence in the optimal process plan. "X,Y,Z" stands for MPS ID, Direction and Tool ID.

Acknowledgement

We thank MAZAK Foundation for its support and Prof. Rei Hino, Nagoya University, Japan, for his advice.


Kristina Kjersem
email: kristina.kjersem@himolde.no

Gabriele H Jünge
email: gabriele.junge@ntnu.no

Improving Planning Process for ETO-projects: A Case Study

Keywords: Last planner system, ETO, Project planning, Earned valuee

This research paper builds on a case study performed at a Norwegian company that deals with a large number of small Engineer-To-Order (ETO) projects. Recently, the company started an improvement process pursuing lean principles. One of the initiatives taken by the company is to improve the present planning process, which lacks a wholeproject view that can give managers a better decision ground. Two important departments, engineering and production, develop project plans that are based on their own specific approaches and with little collaboration between the departments. This paper presents the preliminary results of implementation of Lean Project Planning (LPP), a planning tool developed within shipbuilding industry, a typical ETO environment.

Introduction

Increasing competition on product quality, cost, rapid project delivery while maintaining a certain flexibility during the design, engineering and production phases of a project are a few of the challenges many Norwegian ETO organizations encounter nowadays. In [START_REF] Haartveit | Integration Alternatives for Ship Designers and Shipyards[END_REF], the authors state that this type of industry is "characterized by low-volumes, high degree of customization and project-based processes" which means that the customer is involved from the design phase of a project and can decide specific features of the product all the way to the delivery phase. The case company subject of our research is an ETO organization producing pressurized storage tanks used within industries like shipbuilding, offshore platforms and other similar environments that require such products. The company is located in Norway and it has a good reputation on delivery of highly customized products by offering market design, engineering, manufacturing and testing of the final products. However, the competition on this specific market is increasing and the company focuses now on improving its working processes at every level within the company. The leaders and the employees are all committed to the improvement program and one of the proposed actions is to implement lean ideas that will help them to define a way of working smarter for achieving their goals: Shorter lead-time, lower production costs and better control over their projects. Another focus of the improvement program is on creating a proactive planning process that integrates all disciplines in a common project plan.

However, in traditional project management, the planning activity is often seen only as a technical process neglecting its human aspect and the need for collaboration [START_REF] Ballard | Seminario Internacional de Confiabilidade da Petrobras[END_REF]. In our paper, we argue for implementing a planning tool that combines both technical and human aspects of the planning process in a novel way: Lean Project Planning (LPP). The empirical data suggest that using traditional project management approach is not enough for ETO projects and among the reasons is the number and differences between project participants as well as the iterative nature of design and engineering activities.

The aim of this paper is: 1) to present the case and the challenges experienced by the company before implementing LPP; and 2) to present the preliminary results of implementing LPP. As a planning tool successfully implemented in other complex projects, LPP aims at improving the planning process by creating a project environment that inspires commitment and where open communication and a proactive planning attitude is the norm, not the exception. LPP combines Last Planner System and Earned Value Management concepts in a way that complete each other and give project team a good foundation for the decision process at the management level [START_REF] Emblemsvåg | Lean Project Planning: Using Lean Principles in Project Planning[END_REF][START_REF] Emblemsvåg | Lean Project Planning in Shipbuilding[END_REF] as well at the project level.

Lean Project Planning

Lean Project Planning (LPP) is a management model that has been successfully implemented at Vard, a shipbuilding group in Norway [START_REF] Emblemsvåg | Lean Project Planning in Shipbuilding[END_REF][START_REF] Halse | Implementation of Lean Project Planning: A Knowledge Transfer Perspective[END_REF]. LPP is based on several components : 1) Lean thinking ideas like the PDCA circle; 2) elements from Last Planner System (LPS) [START_REF] Ballard | The Last Planner System of Production Control[END_REF] used within Lean Construction environment; and 3) Earned Value Management (EVM) [START_REF] Sumara | Earned Value-The Next Generation: A Practical Application for Commercial Projects[END_REF] used within project management practice.

LPP as it was implemented since 2009 at Vard Group [START_REF] Emblemsvåg | Lean Project Planning: Using Lean Principles in Project Planning[END_REF][START_REF] Emblemsvåg | Lean Project Planning in Shipbuilding[END_REF]. LPP as a planning method distinguishes the system part and the planning process part within the project planning as a whole. For the system part, an IT tool (Primavera, Microsoft Project, etc.) is used as a planning and reporting structure. The planning process part is based on LPS, EVM elements and lean ideas.

The planning process focuses on collaboration, open communication and involvement from the people allocated to the project. The Project Plan is in fact the project's database as recorded in the IT system and only the planner manages the data in this plan. The plan that is first prepared and is a part of the contract signing is the Milestones Plan. This plan contains key events of the entire project from the contract signing to the delivery of the final product. The next plan is the Discipline Plan, which is created in collaboration among all disciplines (including relevant subcontractors) to be involved in the project. Together, Milestones Plan and Disciplines Plans generate the Master Plan that shows the whole project execution horizon. Activities within these plans are quite general and have a long duration. A more detailed plan is created at the Period Plan level that contains activities with duration between five to eight weeks: A look-ahead plan per discipline.

Due to high number of activities and the need for flexibility at weekly plan level, EVM is applied at the Period Plan level that is a suitable level of detail, consequently making the EVM reporting process quite reliable. By focusing five to eight weeks ahead, the Period Plan gives project organization the possibility to avoid deviations from the plan by removing any constraints before the activity supposed to start. The Period Plan contains work packages that are defined so that they can be used within the EVM planning and reporting procedures. Each supervisor reports on a weekly basis the status of their work packages: Percent physical complete on each activity, remaining hours and, if necessary, a new finish date in case of delays from the plan. During the reporting process the seven preconditions or constraints (Preceding work; Resources; Information; Materials; Space; Tools; External conditions) [START_REF] Hamzeh | Improving Construction Workflowthe Connective Role of Lookahead Planning[END_REF] for an executable activity are analyzed, making people aware of eventual problems that can cause delays. After the reporting process is completed, the project planner creates project reports and sends them to the whole project team and to high-level management.

The Period Plan is further developed into a more detailed plan that is called Week Plan. This is a detailed and dynamic plan created and followed by each supervisor who reports the completion of planned activities during the weekly lean meeting. These lean meetings are steered by the technical or production coordinators and have the purpose of enhancing communication and commitment among project participants. Each lean meeting takes less than one and a half hour and follows a standard procedure so that people involved in more projects know what to relate to. Some general rules for these meetings are: 1) Attendance is not voluntary (all invited people must participate). 2) People must come prepared to the meeting; 3) Line management join the meetings from time to time (supervisors are evaluated on the way they are prepared for the meetings). 4) People have to explain to the rest of the team the status of their own activities, causes for deviations and measures for recovery of deviations (this is important for other disciplines that might need to replan some of their activities) as well as which activities are planned for execution for the next week or two. 5) People must follow the rules of the meeting and are invited to come with suggestions for improvement [START_REF] Emblemsvåg | Lean Project Planning: Using Lean Principles in Project Planning[END_REF].

The system part of LPP as represented in the triangle shows the cost breakdown structure (CBS) and different levels of work packages as implemented in the IT systems: one used for project planning purpose and the other one used for the financial purpose.

The idea behind LPP is according to [START_REF] Emblemsvåg | Lean Project Planning: Using Lean Principles in Project Planning[END_REF], that EVM is good at handling issues at a high level of project management, but fails to handle issues concerning improving project performances relevant to supervisors. Among the critics to EVM within lean construction literature, some authors argue that EVM treat project activities as independent when in fact they are interrelated [START_REF] Kim | Is the Earned-value Method an Enemy of Work Flow[END_REF], and that EVM does not provide indicators on the quality of the construction or the qual-ity of the process [START_REF] Cândido | Critical Analysis on Earned Value Management (EVM) Technique in Building Construction[END_REF]. On the other hand, [START_REF] Olano | Understanding the Relationship Between Planning Reliability and Schedule Performance: A Case Study[END_REF], present an analysis showing that there is a statistic significant correlation between EVM and LPS and recommend to train project managers in the use of both methods in their work. The combination of these two methodologies add value to project planning and control involving and motivating the project team. The strength of LPS is that it systematically handles issues regarding project performance at supervisor level, but do not deal with high-level management issues as well as EVM does [START_REF] Emblemsvåg | Lean Project Planning: Using Lean Principles in Project Planning[END_REF]. An important rule when using LPP is to find the right level of detail for each of the plans. Emblemsvåg [START_REF] Emblemsvåg | Lean Project Planning: Using Lean Principles in Project Planning[END_REF], considering the level of uncertainty in an ETO project, recommends to "train the organization to live with this uncertainty and then rely on the expertise of supervisors and coordinators to maneuver to find the best solution for given circumstances" (p.6). The focus here is on planning as a communication process among all project participants from the lowest to the highest level of decision-making pyramid.

Research Methodology

We apply case study methodology to this research. Yin [START_REF] Yin | Case Study Research: Design and Methods 5th ed[END_REF], states that a case study investigates a contemporary phenomenon in its natural setting and the outcome is on relevant theories generated from understanding gained through observing actual practice. The focus of our research project is on how to improve the planning processes at the case company by using LPP as a method that can help them achieve the desired results: integrated plans. The data is mainly qualitative and we collected it through observations, discussions and interviews as well as frequent participation in day-to-day organ-izational processes related to some of the projects. In addition, one of the authors worked directly with LPP at the shipyard and later with the implementation at the case company. The scope of this paper is to bring to discussion the need for better planning tools for ETO projects as well as presenting preliminary results from implementation of LPP, a planning tool tested only in shipbuilding industry until now. We argue this research contributes to developing a more scientific approach to planning process as a management tool that integrates engineering and production activities performed in complex ETO projects.

Case Company

The case company is an ETO manufacturer offering market design, engineering, project management and manufacturing of pressure vessels, process vessels and storage tanks to the oil and gas market. Products are highly customized and are manufactured at the company location, which can accommodate over 35 projects at a time. Based on the size and complexity of each project it can take from 7-8 months to 12-15 months from the contract to the delivery of a new product. This long project duration include long lead items (e.g. special forged parts that can take up to several months to be delivered). However, based on market demands, the company is interested in shortening this lead-time by improving its working process.

We started the project by carrying out a mapping process that identified the working processes that were most beneficial to improve first. Together with company representatives, we decided to investigate a method for improving the project planning process. Currently, their project planning process is mainly divided in two sections: one performed by the technical manager and one performed by the production manager. There is very little integration between these two plans and the company is interested to achieve a total project overview that can give them a better control over their projects (even though the two departments disagree on the ownership of the total plan).

The organization model applied by the company is mostly line-organization (department leaders are part of the project team and allocate task to own people on a daily/weekly basis) type with only a few people allocated specifically per project. Such type of organization is not usually associated with ETO environment which, according to Gosling and Naim [START_REF] Gosling | Engineer-to-order Supply Chain Management: A Literature Review and Research Agenda[END_REF] is "primarily associated with large, complex project environments such as construction and capital projects"(p.741). However, the case company specifically designs, engineers and manufactures every product according to each customer specifications, which is an important characteristic of an ETO organization. The final products are quite complex and must conform to high quality requirements due to their purpose on offshore platforms, vessels and other specific environments. In addition, an important customer requirement is the possibility to introduce last minute changes to the product while under production.

Shortly before the sale is completed, the sale manager transfers projects to a Project Manager (PM) and, considering that the planning process starts often during the negotiation phase, the results is that the PM has, at the taking-over point, a prearranged milestones plan that is difficult to change.

Resource allocation per project is performed at department manager levels where Technical Manager and Production Manager distribute tasks to people in their departments on a weekly basis by taking into consideration priorities from a project portfolio perspective. That is not always in accordance with each PM own plan for execution of the project. In order to follow their own project plans, each PM applies a certain stress on the engineering and production teams to produce what PM acknowledge as important from own project perspective. When PM comes with some urgent activities for one project, people will delay other activities committed to other projects, and this leads to a constant firefighting working environment. Another important aspect is that having allocated tasks on a weekly basis, employees do not have the possibility to plan and prepare activities so that these will be executed on time. The process of preparing activities is about all the actions and procedures that identify and remove constraints for future work [START_REF] Ballard | Lookahead Planning: The Missing Link in Production Control[END_REF].

The reporting process is performed on a weekly basis and employees report physical percent complete on the allocated activities to the Technical Manager and Production Manager who report further to each PM and other company leaders.

Technical department plans the design and detail engineering activities, which are performed both in Norway and in a foreign European subsidiary. The drawings are produced through an iterative process, as many of them need comments and approval from the customer and from classification societies. The drawing process is also dependent on the footprints from some of the suppliers of valves, pumps and other equipment to be installed inside and outside the tanks. The planning process for the entire engineering department is prepared by the Technical Manager in Norway who plans and allocates activities to all the engineers within the company on a weekly basis. There are no links between the engineering plan and the production plan prepared by the Production Manager for all the projects under execution. Planning of the procurement activities is mainly based on information from the production department and experience from previous project.

Discussion

The first step on the LPP implementation process at the case company started with hiring a planner who mapped the current planning processes and systems existing within the company. The result shows different thinking approaches as well as different IT systems between departments. We identify how different aspects of LPP can handle challenges in the planning process at the case company.

The next step of implementing LPP was to train some of the employees in using the different parts of LPP. However, the training was at a superficial level and did not get into significant details due to a high product order at the time of implementation.

The first department implementing some features of LPP was the production department where they introduced a constraint analysis for their planned activities and the result was a significant improvement in the number of activities completed as planned. According to the project planner, the percent of activities completed as planned before starting the new approach, was between forty five to fifty percent. After starting to use lean meetings and activity constrains analysis, the percent of completed activities increased to over sixty percent and the production department is now working for implementing the EVM reporting per project. However, there are some challenges due to the IT planning system that limits some of the EVM feature (the difficulty to report physical progress). The managers of the company are interested in this methodology and work for defining the best solution.

Another relevant result was an improved communication from people on the production department about which constraints might affect their activities on the near future. The supervisors' involvement and commitment resulted in a requirement for a white board containing weekly-actualized plans to be placed at the production department. These plans are created in collaboration with the production manager, the planner and relevant subcontractors.

The technical department remained reluctant to implementing LPP and one of the reasons is their difficulty and time-consuming planning activities with their iterative nature specific engineering activities. However, the planning process from the production department, showing constraints coming from the technical department, challenged the technical coordinator to take measures for eliminating these.

Overall, the preliminary results of implementing LPP show a significant improvement in the project planning process at our case company especially at the production department. The next step of the implementation is the technical department where we are in the process of defining what their typical constraints are when planning iterative engineering activities. Another aspect we are looking into is how to motivate engineers to plan the completion of their activities in close collaboration with the suppliers of technical documentation.

An important remark here is that the success of LPP implementation on the shipbuilding company was sustained by a dedicated training from the yard management. Without this type of training, the implementation of LPP is slower and the results might come after several projects. The preliminary results on our case company confirm this statement.

The preliminary results endorse also the idea that LPP is an appropriate tool for planning ETO projects and we are looking forward for the next phase of this implementation.

Conclusion and Limitations

In this study, we have investigated the planning process in the manufacturing company who organize and carry out projects in an ETO environment. The current processes have been analyzed and challenges and areas of improvement have been identified. Furthermore, the study demonstrates that LPP as a management model is able to meet these challenges and suggests specific measures to improve the planning process in this company.

By applying LPP principles, the company can first develop a good planning process that motivates people to participate and to make promises they want to keep. Then, in order to complete their activities as promised, people must communicate to each other, find out what can affect their plans and how would they avoid big deviations. However, a good reporting process showing the project status is an important issue both for the project team and for the leaders at the case company. Good routines on estimating budgets and durations must be developed for projects teams and managers.

Moreover, LPP gives leaders the possibility to make decisions based on right information from the people executing the work. Project reports obtained through the EVM elements can also support the managerial decisions by presenting a possible outcome of the project when no recovery measures are taken. LPP is most of all about facilitating a dynamic communication process that enhance the project team capabilities to deal with variation and rapid changes during the project execution. However, implementation of LPP is dependent on the way people understand it and translate it to their working procedures.