Elli Verhulst
email: elli.verhulst@artesis.be

Casper Boks

Bringing About Sustainable Change in Product Development: Theory Versus Practice

Keywords: sustainable design, life cycle thinking, implementation process, implementation approach, case study

Using a change management perspective, this paper studies the implementation process of life cycle thinking and sustainable design in practice, based on empirical data from eight firms involved in product development. The data indicate that different firms take different trajectories and approaches towards implementation, which in turn depends on a number of human factors, including participation of employees, training, resistance to change etc. As a result of this study, a model for the implementation of sustainable design is presented. Firms can use the model and the insights for the improvement and adaptation of existing methodologies and for choosing a fitting approach for integrating life cycle thinking.

Introduction

The translation and implementation of academic theories, concepts and innovations into successful business applications is a well-known challenge. In the field of sustainable design such challenges exist as well [START_REF] Baumann | Mapping the green product development field: engineering, policy and business perspectives[END_REF]. This field has, since the early nineties, passed through a series of transitions, making this implementation process gradually more complex, as these transitions have for example demanded a shift from a product to a systems perspective, from an environmental to a sustainability context, and from concept development to technology transfer and commercialization [START_REF] Boks | Transitions in Sustainable Product Design Research[END_REF]. Academic improvements in addressing sustainability criteria in product development have been proposed by many scholars, often in the form of methods and tools [START_REF] O'hare | Eco-innovation tools for the early stages: an industry-based investigation of tool customization and introduction[END_REF]. Other scholars propose methodologies for sustainable product development -also referred to as life cycle thinking-that suggest when and how sustainability criteria should be taken account of and which tools may (or even should) be used [START_REF] Brezet | Ecodesign: a promising approach to sustainable production and consumption[END_REF]. Most of these tools focus merely on methodological aspects. Moreover, many of these existing roadmaps offer support for pilot initiatives only, and/or are based on pilot studies only, whilst the main challenge lies with moving from successful pilot initiatives to recurring initiatives that lead to long-term sustainability [START_REF] Wilson | Innovating for environment and society: an overview. IIED Briefing Business models for sustainable development[END_REF]. Literature on sustainability in business offers some approaches that cover a long-term implementation process on a general level within the firm [START_REF] Dunphy | Organizational change for corporate sustainability[END_REF]. However in the field of sustainable design, such a holistic view on the complete implementation process is lacking, both from a theoretical and from an empirical perspective.

The field of change management profoundly studies change processes with the aim to support and streamline this complex and lengthy process. A holistic view is thereby taken, whereby methodologies, as well as different approaches and variable influencing factors consider the aim to successfully reach the change. Lewin for example proposed that a process of change can be divided into three stages: unfreezing, changing and refreezing [START_REF] Lewin | Field Theory in social science[END_REF]. There is considerable consensus on this three stages model of organisational change [START_REF] Kanter | Managing change in organisations[END_REF]. Literature on change management also indicates different approaches that can guide an organisation through these subsequent stages of a change process [START_REF] De Caluwé | Leren veranderen. Een handboek voor de veranderkundige[END_REF], [START_REF] Kotter | Choosing strategies for change[END_REF]. These approaches emphasize e.g. a directive, educative or participative approach of the process to reach the goals of the change. Factors that influence a change process can be related to practical and organisational issues, which in turn may have a substantial relationship to personal or emotional factors. This latter group of factors, the human dimension of the implementation process, is so far insufficiently studied in sustainable design research [START_REF] Baumann | Mapping the green product development field: engineering, policy and business perspectives[END_REF][START_REF] Verhulst | The human side of Ecodesign from the Perspective of Change Management[END_REF][START_REF] Boks | New academic research topics to further ecodesign implementation: an overview[END_REF][START_REF] Boks | The Soft Side of Ecodesign[END_REF]. This human dimension forms the subject of a broader study that focuses on human factors and how they influence the implementation process of sustainability criteria in product development [START_REF] Verhulst | Colour-print thinking to measure and support human factors in the implementation process of sustainability criteria in design[END_REF], [START_REF] Verhulst | The role of human aspects in design for sustainability strategies and approaches[END_REF]. This paper forms a part of that study, but limits its focus to the implementation approach that is followed and the process steps that are taken during this specific implementation process.

The aim of this paper is to provide insights -based on an empirical study -on the overall implementation process of integrating life cycle thinking in product development and on approaches that can be taken to reach the sustainability targets. Knowledge on change management is thereby used to broaden insights on the followed trajectories in business. Two research questions are formulated: I. Which steps are taken in the implementation process of sustainability criteria in product development that support the transformation of academic knowledge into practical applications? II. Which approaches are used for the implementation process of sustainability criteria in product development?

Research approach

A qualitative case study research approach is used to provide answers to the two research questions and to offer insights on similarities and distinctions between different firms on the implementation process. The empirical data are also used to shed light on the specificity of sustainability as the subject of the incorporation process. Apart from a geographical location in the Benelux for practical reasons, two criteria have been used to select eight case study firms, making it possible to obtain a good understanding of the phenomenon under study [START_REF] Patton | Qualitative Evaluation and Research Methods[END_REF]: firms were selected that incorporate an own product development department, and have taken at least the first steps towards the integration of sustainability criteria in the firm and in product development. Interviews with company representatives related to both product development and the process of implementing sustainability criteria in product development or in the firm are the main source of data, which is supplemented by archive data, company documentation and observations [START_REF] Yin | Case Study Research. Design and methods[END_REF]. The analysis of the empirical data has been done in two main stages, of which the first has a descriptive nature, whereas the latter is explanatory. In a first step, different topics that have been touched upon in the data set were coded and subsequently clustered. A second part of this step contained the description of the phenomenon under study, i.e. the implementation process of sustainability in product development, subsequently followed with an analysis of each case. This step provides insights in the approach, activities a firm has gone through in the implementation of sustainability criteria in the firm. In a last step, a cross-case analysis between the different cases was made, subsequently followed by the development of a model for the sustainable design implementation process.

Study findings

The empirical data for this study is based on almost 20 hours of interview data from eight different medium and large sized Belgian and Dutch firms, from various sectors (including the furniture, electronics, chemical and construction industry). These interview data have been supplemented with observations during meetings with the informants, and several documents such as year reports, sustainability reports and folders, and internal documents. From the respondents that cooperated, eight had clearly defined responsibility in implementing sustainability within the firm and the product development process. The functions of these people vary within the different firms: as a coordinator of CSR, coordinator of quality, health and environment, communication manager, or R&D manager.

Process steps

The first research question addressed in this paper concerns the process steps of the implementation process that firms pass in practice. A first stage is indicated in literature to unfreeze or prepare for the change, which in this case is the implementation of sustainable design. Table 1 gives an overview of the activities that the case firms dealt with in this preparatory stage in the eight cases. The table indicates that in only one of the cases, all aspects of the preparatory stage are fulfilled. Knowledge on change management was indicated as a basis for any change to occur in this firm. In the other firms however, one or more aspects of this preparatory stage are not prepared or carried out. In three of the cases, less than two elements have been achieved. The empirical data however indicate that independent initiatives are performed to initiate the integration of sustainability criteria, without the preparatory stage being (fully) achieved. The development of a vision, mission, strategy and planning were thereby indicated in several cases to take place after the completion of these independent initiatives. This indicates that the succession of activities during the first stages of the implementation process differs from the activities of this preparatory stage suggested by literature as conditions for success.

Build change team

Vision and mission

Strategy general level

Strategy for product development Planning

Case 1

x x x x x - Case 2 x x - - x x Case 3 x x - x x x Case 4 - - - - - - Case 5 x x x x x x Case 6 x - x x x x Case 7 - - - - x x Case 8 - - - - x x
The data thus demonstrates that the development of a vision, mission and general strategy are not necessarily needed as a first step, and more importantly, this implies that a product development department can take the role of initiating the integration of sustainability criteria in product development. However, in order to bring the incorporation of sustainability to a higher, broader and permanent level within the firm, the different elements of the preparatory stage need to be further developed and supported by the management, as illustrated by the following quote:

'We first did some independent, smaller projects with external partners, more because we didn't really know what we wanted to do, so more isolated initiatives. But now there has been decided to take a look at sustainability more profoundly, especially towards the end of the lifecycle of our products. This direction comes from the top management, but the projects are proposed by the R&D managers.' (product developer of case 7)

A second stage in a change process -described as the change stage in literature on change management-includes several interventions. In all cases, different activities, projects and actions that are considered to support changes towards sustainability in the firms, were found to take place in the eight case firms. Different interventions were indicated to take place simultaneously as well as consecutively. This suggests that completing a pilot project functions rather as a startup of the implementation of sustainability criteria in product development, but also that multiple product development processes need to be performed before full integration of sustainability criteria in design can be reached. Five types of interventions are identified to occur in practice: product development projects with specific sustainability goals (in cases 1, 2 and 7) are projects that focus specifically on certain aspects of sustainability, e.g. on the recyclability of the product's materials. Such projects are considered to run parallel with other, generic product development projects within the firm. Product development projects with sustainability criteria incorporated in the firm's product development process. In four of the cases, an adapted methodology was developed and spread throughout the employees within or connected with the product development department. In case 3 for example, sustainability criteria that fit the priorities of the firm, i.e. recyclability of materials, have been included in the different product development process steps starting from the product specifications. In this firm, small but continuous improvements lead to further integration of sustainability criteria in the product development process. In several of the cases, specific sustainability projects occur on a general level within the firm. This type of project is directed to raise awareness with the employees on sustainability issues, e.g. a yearly social day (case 7), to improve the overall sustainable profile of the firm, such as efforts on energy-efficiency (case 7), or to improve the overall sustainable image of the firm, such as brochures on sustainability in the firm (cases 3 and 5) or a (renewed) website with sustainability information (case 3

Implementation approach

The second research question in this paper concerns the implementation approach that is applied in practice for incorporating sustainability criteria in product development. Table 2 offers an overview of the implementation approaches used in the eight cases in this study. The empirical data indicate that few of the firms use a generic approach for incorporating sustainability criteria as 'a change as many others', whereby an approach is consciously used that supports all changes that occur within that specific firm (cases 2 and 5):

'We identify the issue -like the green stuff-we find an approach, we run a pilot, we map it on the process, we update procedures and then we identify the training needs. That is done for all changes here. We always go through that same cycle.' (case 2)

All firms however adapted the implementation approach to the firm's culture. An adaptation to the firm's culture is mentioned in literature as an important point of attention to raise the chance of successful implementation [START_REF] Kotter | Choosing strategies for change[END_REF]. In practice, this adaptation seems to occur naturally, but not always consciously. The data indicate that this leads to interesting differences in approaches that emphasize other elements of the implementation process. In case 4, the creation of new challenges formed the main element of sustainable innovations. In some cases, control, structure and organization form the dominant characteristic in the applied approach (cases 2 and 5), whilst in other cases, the employees are considered as a central element in the process, whereby change is seen as a shift in human behaviour (cases 1 and 3). In half of the cases, change is considered mostly as a learning process, whereby the motivation and learning capacity of the employees is seen as an important element that can provide the changes needed (cases 2, 6, 7 and 8). The empirical data thus indicate that different approaches can lead towards sustainability in product development, depending on the culture of a firm. On the other hand, the subject of change -sustainability criteria in product development -also implies specific points of interest that need attention during the implementation process, such as the complexity of the subject, a lack of clarity on the concept of sustainability and a lack of clear and uniform measurement systems. This adaptation to the subject of sustainability seems to occur less in the firms studied.

Discussion

The empirical data in this study indicate a different order of activities during the implementation process of life cycle thinking in design in practice, than the order of activities as suggested in literature, especially in the unfreeze stage. In practice, this stage consists of independent projects that include sustainability aspects, whereas in literature, this unfreeze stage entails the development of a vision, mission, strategy, etc. These activities are indicated to take place in the cases, but often after completion of several of the individual projects. Several interventions are mentioned in the data set to take place both in the unfreezing as in the change stage, whereby different types of projects occur that support the translation of academic knowledge into practical applications. Some of these projects aim at passing theory and knowledge on sustainable design towards employees and partners, whilst other projects aim at supporting the implementation process and its approach. In all cases, external partnerships, amongst others with universities, are created to strengthen the link between theory on sustainable design and its application in the firm. This type of projects is thus recognized in all cases, but might need further exploration to support the implementation process more profoundly. The insights on the implementation process steps and approaches, together with the results of a broader study on the implementation of sustainable design, have been used as input for the development of a descriptive model. This model shows the main process stages of the implementation sustainable design, as well as it includes human factors that came forward in the broader study. The model combines theoretical insights that have been gathered in a review of sustainable design and change management literature-with the understandings that were gained in practice. This combination of theoretical and empirical insights offers valuable indications on the process steps and human factors for scholars and practitioners to raise their understanding on the implementation process of sustainable design and the human factors within (Fig. 1).

Fig. 1. Model on sustainable design implementation

The model consists of three circles that represent I) the implementation process steps in the inner circle, II) human factors that have been indicated as significant to take account of in each process step, represented in the middle circle, and III) employees or departments that come forward in the study to be involved in the corresponding step of the implementation process, represented in the outer circle. The inner circle offers an overview of the implementation process on a long term. It indicates how firms evolve from one or more pilot projects on sustainable design towards an integrated sustainable design process. The model thereby places the product development process in the broader perspective of the implementation process. Apart from the process stages in the inner circle, the model presents which human factors are indicated in the study as significant to be incorporated or taken account of in the different implementation stages, such as engaging employees. Several of these human factors appeared to be recurrent in the different stages, e.g. in the subsequent interventions, but directed to another -and growing-group of employees. This expansion of the group of employees involved explains the importance of the third circle in the model, which shows the (new) employees or departments on which the human factors are indicated to apply to, as for those people, that moment forms the start of the implementation of sustainable design. The outer circle also indicates a small number of employees that is indicated to be involved in the beginning of the implementation process. This group of employees is found to grow slowly at first, but suddenly this growth was indicated to be much faster after the development of a general vision and strategy on sustainability in product development and in the firm.

Further research could focus on a validation of the descriptive model by applying it in practice from the start of the implementation process of sustainable design and measuring the success of the process. Another direction for future research is suggested to focus on the implementation process of sustainable design in firms that are active in the same sector and that have a similar organisational culture, with a focus on the choice and application of a specific implementation approach in comparable situations.

Conclusion

This paper studies the implementation process of life cycle thinking in practice, starting from empirical data. Knowledge on change management is thereby used to shed light on the processes that occur and the approaches that are taken by the participating firms. The knowledge from change management and the empirical data together provide a holistic view on the complete implementation process in practice, which is currently lacking in the field of sustainable design, both from a theoretical point of view as from an empirical perspective. This study indicates that different trajectories are followed that depend on the context of the firm. Moreover, variable approaches are indicated to occur in practice in which differences in emphasis are put on methodology, participation of employees, training, etc. A descriptive model is presented in the paper that shows the relationships between three levels in the implementation process of sustainable design: process, human factors and employees and departments involved. It offers a visual overview on how the process can be approached on these three levels. To both firms and scholars, this model and the insights from this study for the improvement and adaptation of existing methodologies may be useful for both scholars and firms, and guide them in choosing a fitting approach for integrating life cycle thinking in product development.

Table 1 .

 1 Overview of activities in preparatory stage

	Case	Establish need for sustainability

  ). Research projects on the subject of sustainability occurred in all cases. In cases 2 and 7, this occurs in the own research department of the firm, as well as in cooperation with external experts and partners. All firms indicated to cooperate with research institutes and universities, either by collaborating in research projects or by outsourcing research to those institutes that are aimed at improving sustainability efforts in the firm. This sort of intervention broadens the knowledge on certain sustainability aspects and strengthens the external

network. Interventions that aim at supporting the overall implementation process of sustainability criteria in product development are interventions that are not necessarily related to product development projects or to the subject of sustainability, but that are considered to support the implementation process. Training and communication are two examples of such interventions (cases 1, 2, 3 and 5).

Table 2 .

 2 Implementation approach used in eight cases, criteria based on[START_REF] De Caluwé | Leren veranderen. Een handboek voor de veranderkundige[END_REF]

	Cases	Implementation approach
	Case 1	People are central
		Change is seen as change in human behaviour
		Return is respect and appreciation
		Empowerment of people is important
		Involvement of all employees is the goal
	Case 2	Changing is learning: change people with own motivation and learning capacity
		Only people that come in contact with product development (PD) and
		sustainability issues are involved and trained
		Many procedures are used and followed
		'Learning from mistakes'
	Case 3	People are central
		Change is seen as change in human behaviour
		Return is respect and appreciation
		Empowerment of product development department is high
		Product development and sales are strongly involved, production less


Çagatay Iris
email: ciris@itu.edu.tr

Mehmet Mutlu Yenisey
email: yenisey@itu.edu.tr

An Efficient Heuristic Algorithm for Capacitated Lot Sizing Problem with Overtime Decisions

Keywords: Production Planning, Lot Sizing with Overtime Decisions, Global Search, Simulated Annealing

Capacitated Lot Sizing Problem is a very important tactical level decision making problem that answers the questions of producing when and how many in dynamic demand environment. Solving Capacitated Lot Sizing Problem with Overtime decisions (CLSPO) and extensions derived from the fundamental structure optimally suffer from combinatorial nature of the problem. The aim of the study is to form a two-stage heuristic algorithm to solve related problem in polynomial time. In first part, characteristics of problem structure are presented. Dominance properties are presented to help algorithm obtain a bounded search area. Proposed algorithm directly utilizes such shortcoming. Performance of approach is tested by using different criteria. And finally, robustness test are applied to check how well algorithm performs against fluctuations in its data. Simulated annealing as improvement heuristic performs well for related problem. It is also observed that fluctuations of data directly affects performance outcome. Obtained results also reveal that performance of improvement heuristic highly depends on constructive heuristic. Algorithm is also applied to an industry case study to plan master production schedule with minimum costs.

Introduction

As the increase in competition, the importance of efficient planning has rapidly increased. Companies in this sense focus on how to reduce production cost by efficiently planning production systems. The difficulty in optimizing planning of production relies on two different tight constraints. Solutions found should be feasible with capacity of period and inventory balance between consecutive periods [START_REF] Tempelmeier | A Lagrangean-based Heuristic for Dynamic Multilevel Multiitem Constrained Lotsizing with Setup Times[END_REF]. CLSP may be enlarged with different types of product structures, setup time, overtime, backlogging, lead times, time windows, planning horizon etc. The resulting combination of alternatives becomes more complicated. It is shown that finding a feasible solution becomes NP-complete whenever setup times are incorporated into model [START_REF] Ozdamar | An integrated Lagrangean relaxation-simulated annealing approach to the multi-level multi-item capacitated lot sizing problem[END_REF]. In most of studies, objective function of problem is formulated as a minimization of production, holding, setup, overtime and backlogging costs [START_REF] Ozdamar | The capacitated lot sizing problem with overtime decisions and setup times[END_REF].

Traditional CLSP and extensions derived from main structure have attracted the attention of researchers over the last fifty years. Reference [START_REF] Bahl | Determining lot sizes and resource requirements: A review[END_REF] clusters lot sizing problems regarding demand type and resource constraint. The fundamental aspects covered in this survey. However, it isn't sufficient to reflect problem characteristics by only focusing on problem structure. Reference [START_REF] Jans | Modelling Industrial Lot Sizing Problems: a Review[END_REF] gives detailed information on solution strategies for CLSP problem. Heuristics and Metaheuristics are most common solution strategies. Simulated Annealing, Genetic Algorithms and Lagrangean Relaxation are apparently most popular techniques for related problem type. It is deduced that neighborhood structures proposed for CLSP apparently performs well for such heuristics. One of the most familiar researches in literature to ours was published in 2000. In the paper, an integrated lagrangean relaxationsimulated annealing approach was presented. However, related study lacks efficient search strategies and real-life implementation [START_REF] Ozdamar | An integrated Lagrangean relaxation-simulated annealing approach to the multi-level multi-item capacitated lot sizing problem[END_REF].

Our study aims at combine a very "easy to implement algorithm" which is lot-forlot (LFL) and global search procedures to solve CLSPO. Lot-for-Lot heuristic which neglects capacity constraint while maintaining inventory balance equations is employed to find an initial solution. The results derived from this phase have been given as an input for improvement heuristic. Global search procedure is capable to improve given initial solution within the feasible solution. The philosophy maintained in improvement heuristic is transferring some amounts of lots from one period to another. Simulated annealing (SA) has been utilized not get stuck in local optimum.

Problem Structure and Dominance Properties

The paper focuses on CLSP in two further aspects. It assumes that two sources of capacity exist as regular time and overtime. Since, overtime and regular time has different costs, basic model should be extended. The related mathematical model is:

= Σ Σ ( ,t, , + ℎ , , + + ) (1)
. . ,-1 + , -, = ,

Σ ,t ≤ + (3) ≤ (2)
Ot ≤ MaxOt t

(5)

,≥ 0, , ≥ 0, ≥ 0, ≥ 0 , (6)
The model covers multiple-items with single-level product structure to be planned over T periods. The objective (1) aims to minimize total cost of production, holding, regular and overtime. Constraint (2) is inventory balance equation for each product and period. Due to the fact that, there are two different resources, capacity limitations formulated by constraint (3) consist of production time with an upper bound of threshold of regular and overtime. Constraint (4) and (5) are control parameters to limit maximum available regular time and overtime. Constraint set (6) reflects nonnegativity conditions.

It should be emphasized that lot sizing problem for single-level product structures doesn't require setup time as an individual parameter because most commonly, setup times do not change between periods. Hence, setup times are included in unit processing time of each product.

A tradeoff between cost of working with overtime and holding a unit of inventory in stock occurs in periods where demand result in idle capacity. It may be logical to produce more and hold inventory rather than using overtime in such peak periods [START_REF] Ozdamar | The capacitated lot sizing problem with overtime decisions and setup times[END_REF]. Hence, proposed neighborhood strategy is based on transferring lots from one period to another regarding such tradeoffs. SA controls the amount tradeoff before taking a move, thus it is considered to be a proper metaheuristic for such neighborhood structures. More precisely, hierarchy of decisions to shift a lot to another period is determined by considering cost parameters of predecessor and successor period in SA [START_REF] Ozdamar | An integrated Lagrangean relaxation-simulated annealing approach to the multi-level multi-item capacitated lot sizing problem[END_REF]. In improvement heuristic, a move is generated by transferring a lot between periods in order to restore feasibility of capacity constraint or improve objective function. It depends totally on the constructive heuristic solution whether to improve objective function or attaining capacity feasibility. Since, LFL heuristic may produce capacity infeasible solution, a control mechanism is adopted.

There are three fundamental decisions that should be made: period to shift a lot from/to, item that will be shifted and amount of transfer. After determining the period and item that will be shifted, amount of lot that will be transferred may be determined. Transferring a lot between periods will result in a cost fluctuation by changing the indices of related cost parameter. Forming a dominance property on one-at-a-time lot transferring may be useful for problem structure. These properties help to limit search space, and results in high efficiency in search procedures.

Dominance properties: Z = f(c 1 ,c 2 ,…,c n ) is the value of measure (objective function in our case) that characterizes iteration S and that Z' = f(c 1 ',c 2 ',…,c n ') represents the value of the same measure under some different iterations S'. Then, dominance set is applied as long as condition Z' ≥ Z implies that c j ' ≥ c j for some parameters j [START_REF] Baker | Introduction to Sequencing and Scheduling[END_REF].

Property-1: Transferring an amount of Δ (Delta) from t 2 to t 1 is dominance property-1 as: Property-1.1: (where t 1 ≤ t 2 and t 2 is most overloaded period in respect to C t2 +O t2 ); Property-1.2:

= { { ,1 +ℎ , 1 -, 2 -ℎ , 2 } } (7) ℎ { ,2 * ℎ } (8)
Starting from the period with highest load and item with highest gap in total holding and production cost with previous period will form a dominance set for backward scheduling procedure. Here function of otherwise reflects whether the related production quantity is adequate. If X i,t2 equals to zero, then there is no proper lot to be shifted from t 2 to t 1 . Product with highest capacity consumption is selected to be shifted in such cases. If X i,t2 still doesn't change, a random product may be selected for shifting procedure. Those factors that don't belong to dominant set will be clarified in algorithm explanations.

After determining the periods to transfer the lot in between and item to be transferred, amount that may be shifted may be calculated. There are two alternatives on transferring a lot. Direction of transfer may be forward or backward. Amounts that may be transferred purely depend upon forward or backward procedure. As mentioned above, constructive heuristic is lot-for-lot, so there will be no inventory on hand at the start of each period in initial solution. Therefore, backward transferring of production lots will be sensible by accumulating on hand inventory for improvement heuristic.

Property-2: If decision is to transfer the lot in backward (which means transferring a lot from t+1 (t2) to t (t1)) direction, the maximum quantity that may be shifted depends upon the feasibility of the solution where the search is initiated and in all feasible solutions, the idea is to improve objective function. The maximum quantity of item i to be transferred is [START_REF] Barbarosoğlu | Analysis of solution space-dependent performance of simulated annealing: the case of the multi-level capacitated lot sizing problem[END_REF];

_ = x{0, { , 2 , 1 }} (9)
The maximum quantity that may be shifted from t2 to t1 is limited to the amount of product that is produced in t2 and the available production capacity in t1. The related is calculated by dividing available time in (C t1 +O t1 ) to unit processing time of determined item i which is . However, if decision is to transfer the lot in forward (which means transferring a lot from t (t1) to t+1 (t2)) direction, the maximum quantity that may be shifted depends upon the performance of backward shifting and inventory on-hand in analyzed period t1. The maximum quantity of item i to be transferred is [START_REF] Barbarosoğlu | Analysis of solution space-dependent performance of simulated annealing: the case of the multi-level capacitated lot sizing problem[END_REF];

_ = x{0, { , 1 , 2 } (10)
The maximum quantity that may be shifted from t1 to t2 is limited to the amount of product that is on hand in t1 and the available production capacity in t2. The limitation here is directly related to the initial performance of lot-for-lot schedule. The quantity that will be shifted is determined by using random integer generators between 0 and Delta_max values. [START_REF] Barbarosoğlu | Analysis of solution space-dependent performance of simulated annealing: the case of the multi-level capacitated lot sizing problem[END_REF]

Heuristic Algorithm

As mentioned above, algorithm consists of two consecutive stages. In the first, there is an "easy to implement" constructive heuristic which is lot-for-lot technique. Solution set obtained in first phase (Step 0) are inputs for improvement heuristic. Lotfor-lot technique results in zero on-hand inventories as initial solution, so related improvement algorithm starts with an accumulation strategy with backward shifting.

The following pseudo code gives information about the flow of algorithm:

Step 0: Obtain an initial solution regarding demand by using LFL heuristic, and calculate all of parameters.

Step 1: Find periods where lot transfer take place by dominance property-1.1

Step 2: After determining periods, identify product that will be backward shifted by using holding and production cost savings via dominance property-1.2

Step 3: Calculate maximum possible amount of lot transfer by dominance property-2, determine lot size to be shifted randomly

Step 4: Transfer required production lot between periods, control overall cost change in objective function. If the change in cost is negative, then apply move. Otherwise, calculate simulated annealing parameters

Step 5: If move is rejected, initialize forward shifting procedure, apply step 2 and 3 iteratively, and transfer an amount of production lot to forward periods

The parameters which are underlined will be changed systematically to understand robustness of proposed algorithm. These variations should give information about how well algorithm performs under different circumstances.

Once algorithm obtains an initial solution, improvement heuristic is applied for n times. The number of n is determined as a function of actual stopping criteria. Improvement heuristic initiates backward shifting of lots with aforementioned dominance properties. Some nervousnesses may reveal in this phase. First nervousness of Dominance property-1 considers whether most loaded period (regular and overtime) t2 is 1. If t2 is equal to one, there will be no convenient period prior to t2. Therefore, a random t should be assigned to update t1 and t2. The step taken by this command may not yield a better solution, but this will help to search for global optimum without getting stuck in local optimum. After that, available capacity for period t1 is calculated, and then maximum quantity of item i which can be shifted without violating feasibility of available capacity is calculated.

Exact amount of transfer is determined by using dominance property-2. Whenever a step is taken, the value of objective function is updated. If there is an improvement in the objective function, new values are set as solution. Otherwise, (Φ cost ≥ 0), PA, tSA values are calculated according to geometric cooling schedule formulated in [START_REF] Ozdamar | An integrated Lagrangean relaxation-simulated annealing approach to the multi-level multi-item capacitated lot sizing problem[END_REF]- [START_REF] Tang | Simulated annealing in lot sizing problems[END_REF]. If the related parameter is greater than threshold value, the move is accepted. Otherwise, lots are transferred from period t to t+m (where m is a random integer between 1 and T-1) to overwhelm problems derived from backward shifting. The adjustments made by forward shifting are directly applied without assessment.

Computational Tests

Computational tests are executed on a personal computer with Intelcore i5, 2.53 GHz, 64 byte. Performance of algorithm is checked with two classes of problem sets. Class A problems are used to control optimality, while Class B is intended to reflect characteristics of algorithm for bigger problem instances [START_REF] Tempelmeier | A Lagrangean-based Heuristic for Dynamic Multilevel Multiitem Constrained Lotsizing with Setup Times[END_REF]. The related problem type is not studied in pervious literature. Hence, data are produced with special predetermined characteristics.

The tests of optimality (Class A) consist of 4 items, 4 periods. These set of data are used to understand how well the proposed algorithm approaches to optimal solution. Class A consists of 20 different data sets. Demands of items are normally distributed with a mean of 140 units and a standard deviation of 60. The factor h/ov is held in two levels as 1.1 and 0.9. To reflect different types of products in the data set, 4 different levels of c/h are imposed in each period. Item1 has a c/h with a mean of 12 and a standard deviation of 8. Item1 represents products with higher production cost respect to holding cost. Item2 has a c/h ratio with mean 14 and a standard deviation of 12.

These types of products have huge deviations in each period in c/h level. That means for item2, there is a great fluctuation in its data for each period. For item3, the ratio is normally distributed with a mean of 7 and standard deviation of 3. Item4 has a c/h with a mean of 2 and standard deviation of 1. These types of products represent the items with high holding costs. The performance of algorithm is evaluated by using 5 different performance measures in Table 1. (Z is the objective function value of given alternative (H: Heuristic, O: Optimal, C: Lot-for-Lot)) The related data set is analyzed in detail and it is found out that algorithm performs quite well in CLSPO. It is also understood that solution set cannot be improved if constructive heuristic yields a GAP 2 value lower than 8 percent. Due to the fact that, lot-for-lot doesn't guarantee a capacity feasible initial solution, performance criteria based on constructive heuristic may yield some misunderstandings. Overall heuristic performance highly depends on characteristics of initial solution. Starting with a good initial solution may not yield a proper ending result. The algorithm approximately takes 1 CPU second to solve the problem. For Class A type problems total numbers of iterations have not exceeded 50 in each run. The number of optimal solution obtained by using algorithm is one for this data set.

Larger instance data is collected from a propeller shaft production company, and two different sub-classes are formed. In Class B1, 20 periods (5 months in company's MRP system) are planned for 7 different basic products. In Class B2, 35 different items have been scheduled in 6 production periods. Results obtained are evaluated with two different characteristics. One of them is actual stopping criterion and other is CPU seconds. For Class B1, algorithm mostly stopped by maximum number of iteration criterion which is fixed at 5000 for each run to facilitate a fair comparison. Approximate time to obtain a result is 8-15 CPU seconds for Class B1. Company plans to schedule its production based on %70 of its product mix. Hence, other class contains more products. Most of runs in Class B2 stopped by losing forward move capability because of high number of products within short planning horizon. For this set of problem, approximate solution time is 10-20 CPU seconds. These results show that algorithm performs quite well in big problem sets as well. Another critical performance criterion is parametric robustness of algorithm. Given high fluctuations in data with item2, results obtained have low standard deviations in optimal solutions. Further analysis will be made regarding parameter dependent tests about robustness in next phase.

Robustness Tests

The performance of heuristic also depends on robustness of structure. In proposed CLSP heuristic, there are three sources of variability. One of most influential variability is demand pattern of products. Standard deviation of demand (STD) is widely used to test this aspect. Hence, we set three levels of demand deviation (Scenario 1-2-3). The ratio of average production cost to average holding cost is another source (c/h, Scenario 4-7). There are also some other sources of volatility which depends on metaheuristic used by algorithm. Determining the amount of lot to transfer backward or forward between periods is key source of algorithmic variability. The one which is uniform(both), right triangular to Delta_max (forward-backward), right triangular to zero (both shifting direction), and lastly right skewed right triangular for forward shifting and left skewed right triangular for backward shifting (Scenario 8-11). Algorithm simulation of different levels for these characteristics is listed in Table .2. It can be understood that increasing values of coefficient of variation (CV) in demand pattern results in higher overall costs. The first three scenarios also give information about computational efficiency of algorithm. Whenever standard deviation of demand is increased time required to obtain a solution also increases. Scenario 1,5,6,7 have "c/h ratio" fixed at seven while standard deviation is changed. It can be interpreted as; decreasing values of standard deviation in c/h, results in higher overall cost. This result is quite interesting, although given fluctuation in parameters is increased while cost associated is decreased. The underlying reason is capability of algorithm which is a function of dominance properties decreases with lower values of standard deviation. Scenarios 8-11 show us that there is not any specific best performing conditions for Delta pattern. It is also deduced that for scenario 8&10, algorithm performs better. It is found out that fluctuation of input-algorithmic variables directly affect obtained results. These validations help us to understand characteristics of problem better.

Conclusion

In this chapter, a two-stage heuristic algorithm is presented to solve capacitated lot sizing problem with overtime decisions. Results obtained indicate that algorithm is quite satisfactory in respect to optimality tests and computational time. Further robustness test shows that algorithm is very stable against fluctuations in its parameters.

As long as the production planning department has an access to real-time inventory data, the production plan generated by algorithm may be frequently updated or the study may be used as an MPS tool to execute in weekly basis (planning horizon) for such kinds of facilities that mostly have single-level items with continuous production flow. Hence, proposed heuristic procedure may be used as a part of MRP planning tool of facilities where continuous production take place. Future studies will focus on applicability of algorithm to multi-level product structures and optimization of simulated annealing parameters for this problem type.

Table 1 .

 1 Results for Class A problems and deviation from optimality

		Mean	Std. Dev.	Parameters
	GAP 1	3,58	2,85 [(Z H -Z O )/Z O ]*100 (distance of heuristic from optimal)
	GAP 2	18,09 17,16 [(Z C -Z O )/Z O ]*100 (distance of constructive from optimal)
	GAP 3	47,43	26,3	[(Z C -Z H )/Z C ]*100 (distance taken from constructive to heuristic solution)
	GAP 4	54,80 44,44	[(Z H -Z O )/(Z C -Z O )]*100 (distance by heuristic solution to constructive solution)
	GAP 5 4494 $ 3707 [Z

H -Z O ] (cost gap of heuristic from optimal solution)

Table 2 .

 2 Robustness Results for Class A problems

		Deman.	C/H					C/H
	Sce.	Mean	Mean	Min		Delta	Dem.	Mean	Min
	(S)	(STD)	(STD)	COST	S	Pattern	STD	(STD	COST
	1	140(70)	7(3)	114628 8	delta_unif_unif	70	7(3) 114628
	2	140(140) 7(3)	122992 9	delta_triatria_max 210 7(3) 140774
	3	140(210) 7(3)	140390 10 delta_tria_tria_min 70	7(3) 116956
	4	140(70)	1(2)	42486	11 tria_min_tria_max 210 7(3) 140771
	5	140(70)	7(7)	84513
	6	140(70)	7(4)	99732
	7	140(70)	7(1)	155347


Rikke V Matthiesen
email: rikkevm@production.aau.dk

Two distinct theories of production: Lean and Toyota management system

Keywords: Lean, TPS/TMS, translation theory, production philosophy

The paper analyses differences between "lean" and its sister concept "Toyota management system (TMS)" by drawing out deep-rooted theories of production within these two streams of literature. The paper argues that such deep-rooted beliefs should be the first target for organizational transformation as these beliefs provide an important contextual layer for any attempts to transfer organizational practices from one organization to another. Examples of implications in relation to translation are sketched out.

Introduction

The literature on failed transition efforts inspired by Japanese concepts is abundant. Some writers have pointed to aspects of organizational environment, managerial behavior and beliefs, or leadership qualities in order to explain the performance and dynamic capabilities of Toyota. It appears from other analyses however, that lean evades precise definition and communication. Hines et al [START_REF] Hines | Learning to evolve -A review of contemporary lean thinking[END_REF] find that the literature on lean is continuously expanding its focus in terms of scope of application in the supply chain. Liker et al [START_REF] Liker | Bringing Japanese Management Systems to the United States[END_REF] suggest that any core practices of Japanese management systems that is attempted transferred, will need to be integrated with systems and practices in a range of contextual layers in highly context specific ways. In line with this proposition, the expansion of the lean concept [START_REF] Hines | Learning to evolve -A review of contemporary lean thinking[END_REF] may be interpreted as a matter of addressing ever more aspects of Toyota's managerial system in the lean literature.

Uncertainty regarding complicated interactions between various system aspects [START_REF] Liker | Bringing Japanese Management Systems to the United States[END_REF] has resulted in attempts to engage in perfect/complete practice adoption. The underlying assumption is that relevant contextual ties affecting core practices can be addressed if a wide set of peripheral practices are also implemented. This approach is supported by some research, see e.g. [START_REF] Shah | Lean manufacturing: context, practice bundles, and performance[END_REF]. However, there are several risks involved in this approach, and conceptually, it may be neither feasible nor desirable. Several sources acknowledge that Toyota applies an integrated manufacturing and management system. In a sketch of a holistic model of such system, also product features may be included [START_REF] Chan | An Integrative Model of Japanese Manufacturing Techniques[END_REF]. This illustrates the span of TPS. At the same time it has been suggested that TPS may establish a carefully designed configuration of job characteristics that lead to worker motivation and positive employee outcomes required to operate other aspects of TPS [START_REF] De Treville | Could lean production job design be intrinsically motivating? Contextual, configurational, and levels-of-analysis issues[END_REF]. In combination, these sources emphasize that TPS is not a discrete set of practices, a system perspective may be more appropriate. However, how to codify and transfer a system from one context to another?

Theoretical Background

The current approach found in lean literature tends to isolate sets of practices and present these as representative of the entire system. This approach falls in the category of analytical reduction; assuming the whole can be studied by studying the characteristics of the pieces. Such approach may be helpful in understanding how different practices work. But it is not helpful as the basis for organizational transformation. Any practice may in its implementation and use be distorted to reproduce former managerial assumptions [START_REF] Lozeau | The corruption of managerial techniques by organizations[END_REF] and they may be selected and/or enacted so that unfamiliar ideas are not adopted [START_REF] Spencer | Models of organization and total quality management: A comparison and critical evaluation[END_REF]. So while TPS may be conceptualized as a system of practices, organizational transformation on the other hand cannot be conceptualized as practice adoption. Selective practice adoption may not lead to the context specific configurations required to obtain the desired systems effects.

Concept Driven Change and Organizational Transformation

Gustavsen et al [START_REF] Gustavsen | Concept-driven Development and the Organization of the Process of Change: An Evaluation of the Swedish Work Life Fund[END_REF] describe the Japanese inspired change efforts as "concept driven" and characterize this type of change as widely communication driven. With communication as the change driver, translation theories show their relevance. Within translation theory, Røvik [START_REF] Røvik | Trender og translasjoner: ideer som former det 21. århundrets organisasjon[END_REF] describes the process of adopting managerial concepts as that of interpreting practices. In this process, practices may undergo considerable transformation either purposefully or unintended as referred to above. Therefore, as argued above, organizational transformation inspired by Toyota should not be seen as a matter of decontextualizing and transferring practices from one system to another. Instead, there is a need for re-conceptualizing content and context.

Design Principles As a Contextual Layer

Traditionally, contextual layers have been thought of as related to physical and institutional scope such as e.g. wider organizational practices [START_REF] Liker | Bringing Japanese Management Systems to the United States[END_REF], laws and regulations, or cultural traits [START_REF] Røvik | Trender og translasjoner: ideer som former det 21. århundrets organisasjon[END_REF]. Spear however, suggests that TPS practices should be considered artefacts of a certain set of system design principles applied within Toyota [START_REF] Spear | Just-in-Time in practice at Toyota: Rules-in-Use for building selfdiagnostic, adaptive work-systems[END_REF]. Within production and operations management, such system design principles could be seen as a more subject-relevant contextual layer influencing how production and operations practices are identified, captured, transferred, and managed across organizations. This implies that organizational transformation inspired by Toyota should be viewed as a matter of transferring concepts and design principles in use from one organization to another. At present, the literature on TPS production techniques (lean literature) function as one of two contexts for our understanding of Toyota. Another context is the literature on organizational aspects within TMS and Japanese management systems. Unfortunately these two streams are poorly integrated. The aim of this paper is to identify the sets of deep-rooted beliefs that these streams of literature explicitly or implicitly represent in order to facilitate future integration.

Theories of Production As the Underlying Context

The objectives of the paper call for a framework that provides sufficient level of abstraction to handle the diverse perspectives or traditions. The paper proposes that such framework may be found in the work by Koskela [11] who proposes to address production theories at three levels:

1. A conceptualization of production. 2. Universal laws and causal relations that would apply under the specific conceptualization of production. 3. Design, control and improvement principles that follow from these causal relations.

Using this theoretical framework, Koskela identifies the deep-rooted beliefs held within three different production theories, among these the production theory that prevailed in the West before the strong orientation towards Japanese manufacturing as well as lean. This is detailed below. Using this framework, design principles as identified by Spear [START_REF] Spear | Just-in-Time in practice at Toyota: Rules-in-Use for building selfdiagnostic, adaptive work-systems[END_REF] are positioned as stemming from more fundamental beliefs about production. In order to identify the overarching conceptualization of production within TMS that matches these system design principles, a review of a narrow set of writings on TMS is conducted. First the application of the framework on lean literature will be detailed.

Theories of Lean Production

Koskela [START_REF] Koskela | An exploration towards a production theory and its application to construction[END_REF] describes the production theory that previously prevailed in the West as a transformation perspective. In this perspective, production is seen as a set of resource consuming transformation activities (cost centers) that should be optimized in terms of input/output. It is assumed within this perspective, that the entire transformation process can be subdivided into sub-processes which are also transformation processes and that the resources put into the set of individual transformation activities determine the overall cost of an item. I.e. sub-processes are considered to be independent.

Koskela characterizes Japanese manufacturing as embedding a flow perspective. In this perspective, time, not only as a dimension for coordination, but also as a valuable resource, is introduced into production theory. The notion of time as a resource allows us to see production as a coordinated flow of materials (level 1 in a production theory). This is a conceptualization of production distinct from the former Western conceptualization. It establishes queuing analysis as the set of governing laws (level 2 in a production theory). These laws establish the link between variability and deteriorated performance in terms of WIP levels, lead times, variable process times, and less than optimal capacity utilization [START_REF] Hopp | Factory Physics: Foundations of Manufacturing Management[END_REF]. Hopp & Spearman [START_REF] Hopp | Factory Physics: Foundations of Manufacturing Management[END_REF] suggest that lean production is aimed at minimizing the cost of buffering variability which can be achieved by a combination of intelligent buffer switching, use of flexible resources, and variability reduction (level 3 in a production theory). Understanding these fundamental design, control and improvement principles, a wide range of lean tools and techniques can be argued for theoretically instead of dogmatically.

4

Theories of Production within TMS Koskela points out that he presents "a 'pure' production theory [which] focuses just on the act of production. It does not deal with such issues as what is the nature of machines or humans as workers or how production should be divided among individuals (the problem of organizing)." (p28) [START_REF] Koskela | An exploration towards a production theory and its application to construction[END_REF]. However, with a "pure production theory" as a starting point, the role of the wider organization including HR may easily be reduced to that of providing conditions favorable to smooth production. This includes the emphasis on HRM practices for ensuring employee motivation and worker flexibility found in previous lean literature. Broader issues of organizing are precisely the concern of literature on TMS. However, as indicated above, a theory of production within TMS is missing. In the following, work by de Treville and by Spear is reviewed in order to establish requirements for a theory of production within TMS.

In her PhD thesis [START_REF] De Treville | Disruption, learning, and system improvement in just-in-time manufacturing[END_REF], de Treville investigated JIT implementations and developed a typology of JIT systems as combinations of JIT flow control and either of the two elements: Flexible resources for improved line balance, and/or learning through disruptions occurring at less than optimal buffer levels. She argued that the application of JIT flow control alone would not lead to the ideal rate of learning (process improvement). She also argued that disruption as means for learning should primarily be applied in situations where production inefficiencies could not be found analytically. This implies situations in which queuing analyses may explain relationships between variability and deteriorated throughput rates but will not suffice to identify leverage points in the system. In her analysis of a set of JIT implementation cases, she found that learning through forced disruptions needs to be carefully managed. Otherwise this practice will lead to unnecessary productivity losses which will stress organizations that, in line with the transformation perspective, have been used to keeping all resources busy at all times and fail to see these disruptions as valuable sources of information. In [START_REF] De Treville | Could lean production job design be intrinsically motivating? Contextual, configurational, and levels-of-analysis issues[END_REF] she furthermore position respect for people, the establishment of good job characteristics and motivation as an important subsystem of TPS in line with lean material flow. In regards to the establishment of a theory of production within TMS the key take aways from this work may be suggested to be:  Proper operation of JIT requires a willingness to invest in learning by exchanging short term productivity for information in order to obtain long term productivity gains. "All other aspects of JIT can be supported using traditional arguments" (p1-16) [START_REF] De Treville | Disruption, learning, and system improvement in just-in-time manufacturing[END_REF].  Idle workers may be seen as a resource rather than an issue. Cross training for improved line balance may also be considered a type of learning that can arise from buffer removal. [START_REF] De Treville | Disruption, learning, and system improvement in just-in-time manufacturing[END_REF]. I.e. there are multiple ways of building up organizational resources associated with JIT practices.  Using disruptions for learning requires careful management of improvement activities and buffers to avoid unnecessary productivity losses and organizational stress [START_REF] De Treville | Disruption, learning, and system improvement in just-in-time manufacturing[END_REF].  JIT is constituted not of one system per plant or material flow but of one system between each two production groups. "A separate decision as to the "best" type of JIT must be made for every intermediate buffer." (p4-25) [START_REF] De Treville | Disruption, learning, and system improvement in just-in-time manufacturing[END_REF]. I.e. the application of JIT systems require significant amounts of context specific design choices.  Employee motivation and respect are important subsystems of TPS. Worker motivation in a lean environment using job standards is especially dependent on the experience of skill variety and responsible autonomy [START_REF] De Treville | Could lean production job design be intrinsically motivating? Contextual, configurational, and levels-of-analysis issues[END_REF]. I.e. application of lean production practices requires careful application of HR practices.

In the following, work by Spear [START_REF] Spear | Decoding the DNA of the Toyota Production System[END_REF][START_REF] Spear | Just-in-Time in practice at Toyota: Rules-in-Use for building selfdiagnostic, adaptive work-systems[END_REF][START_REF] Spear | The High Velocity Edge, How market leaders leverage operational excellence to beat the competition[END_REF] is reviewed. Spear & Bowen [START_REF] Spear | Decoding the DNA of the Toyota Production System[END_REF] describe Toyota as a community of scientists conducting scientific experiments. Spear [START_REF] Spear | Just-in-Time in practice at Toyota: Rules-in-Use for building selfdiagnostic, adaptive work-systems[END_REF] argues that constant application of rules-in-use (specify, build in tests and improve) to system design constitute meta routines that create "highly situated learning that is both broadly distributed" (p2) and where "learning … occurs through frequent practice that allows for repeated failure" (p23) [START_REF] Spear | Just-in-Time in practice at Toyota: Rules-in-Use for building selfdiagnostic, adaptive work-systems[END_REF]. Spear [START_REF] Spear | The High Velocity Edge, How market leaders leverage operational excellence to beat the competition[END_REF] state that "The point of process improvement is to improve the participants' processimprovement capabilities by coaching them as they try to improve the process." (ibid p218). Toyota furthermore takes significant care to extract and disseminate learning from this process [START_REF] Spear | The High Velocity Edge, How market leaders leverage operational excellence to beat the competition[END_REF]. Engagement in Toyota style process improvement is thus a means for improving individual processes as well as a means for accumulating organizational resources in terms of individual skills for process improvement and in terms of widely distributed deep process and design knowledge. With these byproducts of process improvement, Spear reverses the roles of organization and production: "The factory was not only a place to produce physical products, it was also a place to learn how to produce those products and [...] keep learning how to produce those products." (p15) [START_REF] Spear | The High Velocity Edge, How market leaders leverage operational excellence to beat the competition[END_REF]. In regards to the establishment of a theory of production within TMS, the following should be emphasized:

 System design rules that work to reduce variability combined with strict specification allows for detection of and learning about process inefficiencies. [14]  Production may be thought of as repetitive activities that through permutations provide learning opportunities for the organization. [START_REF] Spear | The High Velocity Edge, How market leaders leverage operational excellence to beat the competition[END_REF]  Learning opportunities should be exploited to create better process designs and build resources in terms of process improvement skills in the individual, and in terms of accumulated process knowledge. [START_REF] Spear | The High Velocity Edge, How market leaders leverage operational excellence to beat the competition[END_REF]  The organization not only operates production but also continuously redesigns production. Highly situated learning [START_REF] Spear | Just-in-Time in practice at Toyota: Rules-in-Use for building selfdiagnostic, adaptive work-systems[END_REF] implies highly situated design which requires design knowledge and skills in even the smallest units: The work teams, team leaders etc.

Synthesis

Based on the above, three different theories of production can be sketched. A traditional Western transformation perspective offered by Koskela [START_REF] Koskela | An exploration towards a production theory and its application to construction[END_REF]. A lean production philosophy oriented towards flow offered by Koskela [START_REF] Koskela | An exploration towards a production theory and its application to construction[END_REF] and Hopp & Spearman [START_REF] Hopp | Factory Physics: Foundations of Manufacturing Management[END_REF] in line with industrial engineering reasoning. And a theory of production within TMS, which accommodates for a preference for learning and similar resource based concerns:

1. Production may be conceptualized as a stream of repetitive activities linked through material and information flows, which creates an arena for the organization's continued learning and design efforts. 2. The amount of information that can be extracted from the engagement in production activities depends on the extent to which activities are prespecified, production groups are linked in dedicated flows, relevant buffers are kept small enough for production inefficiencies to trigger disruptions and motivate improvement, as well as employee skills for designing and analyzing production. 3. Design, control and improvement principles should comply with the short term goal of optimizing individual processes in line with the lean production philosophy and with the long term goal of maximizing organizational capabilities for process design.

Implications

These three different theories of production may be regarded as different contexts for the design and management of various subsystems of production. This is exemplified in the following with a focus on HRM as a subsystem.

A transformation perspective may foster a view of labor as cost similar to other resources consumed in the transformation activities. In the extreme, the worker may be thought of as an acquired, temporary resource intended for certain production tasks. Training can extend the skills of the worker and may be a necessary investment required to make full use of the resource. However, there will be a balance between cost of training and process requirements. It follows that training is best invested in skills required for the operation of a limited number of production activities.

In a lean production philosophy, training may be more widely engaged in as multi skilling is a means for balancing production lines. The requirements for such multi skilling changes as the line is improved towards reduced variability. If the lean setup is established through the use of "lean tools", additional training may be required to equip the worker to operate these curious tools (kanbans, SOPs etc). The corresponding system specific knowledge in traditional operations may be tacit (who to contact in case of problems, in which cases is it considered appropriate to contact someone etc) and may not necessarily be accommodated for in the estimation of required training periods. In addition to undertaking work in a prespecified way to keep variability low, the lean production worker may also be engaged in the role as informant: He may be expected to signal process inefficiencies and share information on improvement opportunities. This additional role is not strictly necessary to the operation of a lean production setup but it may be applied as a means for reducing variability.

The TMS inspired theory of production accommodates for a quite different role for the worker. In this philosophy, the skills and knowledge of the worker is not only related to the role as producer and the worker's role in process improvement is not restricted to that of informant. Instead, she may be considered the co-designer of practices that simultaneously create lean processes and facilitate further experimentation and learning. In this process, she is also a learner as she improves her skills for undertaking this role and paradoxically also reduces the need for these skills in the specific production activity as it is gradually being stabilized and codified. Within Toyota, this paradox is resolved through the promise of a more transient role for the employee as indicated in several writings on TPS HRM practices. E.g. workers may be promisedif not life term employment then at least corporate commitment to long term employment [START_REF] Pil | Transferring Competitive Advantage Across Borders. A Study of Japanese Auto Transplants in North America[END_REF], the most competent workers may be deliberately idled and eventually moved to other activities requiring improvement work [START_REF] De Treville | Disruption, learning, and system improvement in just-in-time manufacturing[END_REF] and team leader positions may be filled from within [START_REF] Adler | Hybridization, Human Resource Management at Two Toyota Transplants[END_REF]. Such transient role also works to offset the larger investments in skill development as does the more general nature of these skills compared to the process specific skills emphasized under the transformation perspective.

This proposal for a TMS inspired theory of production may be applied in the attempt to discriminate between practices that are modeled over such theory-in-use versus practices that are modeled over alternative theories of production. Thereby research on TMS inspired organizational transformation may be improved. Presently this research suffer a severe limitation as only an isomorphic adoption of either lean practice or discourse are considered real exemplars of Toyota inspired transformation [START_REF] Pettersen | Translating Lean Production, From Managerial Discourse to Organizational Practice[END_REF].

Conclusions

The paper suggests viewing managerial concepts as the content of organizational transformation, which then becomes a matter of adapting practices to match these concepts rather than that of adopting practices and discourse found in literature. Through the notion of "theories of production" a framework that encompasses and highlights differences between an industrial engineering perspective on Toyota (lean) and organizational theorists' perspectives on Toyota management system is developed. The paper contributes with a theory of production within TMS that is contrasted to both a traditional Western theory of production as well as an industrial engineering theory of Japanese production known as lean production. This proposed theory of production within TMS conceptualizes production as a unique arena for learning and thereby points out a bidirectional link between production and wider organization.