# Controlling Product Variance in a Factory Through the Evaluation of the Factory Life Cycle

Lennart Hingst, Peter Nyhuis

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Lennart Hingst, Peter Nyhuis. Controlling Product Variance in a Factory Through the Evaluation of the Factory Life Cycle. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2022, Gyeongju, South Korea. pp.416-423, 10.1007/978-3-031-16407-1_49. hal-05386097

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# Controlling Product Variance in a Factory Through the Evaluation of the Factory Life Cycle

Lennart Hingst and Peter Nyhuis

Institute of Production Systems and Logistics, Leibniz University Hannover,
30823 Garbsen, Germany
hingst@ifa.uni-hannover.de

**Abstract.** The intensification of competition in the global environment means that companies have to respond more actively to the individual wishes of their customers. The introduction of additional product variants in the course of the factory life cycle increases customer perception and enhances product attractiveness on the market. Decisions on the introduction of product variants are made in sales and development. However, the fields of production and logistics often suffering from product diversity only have limited influence. Once a new product variant has been introduced and the associated investments have been made, a cost remanence results when complexity is reduced. After all, an additional product variant may require an increase in capacity if the current production and logistics concept reaches its limits. The resulting follow-up costs have an impact over the entire factory life cycle. Currently, it is not possible to distinguish between value-creating and value-destroying variant-induced complexity. Therefore, this paper presents an approach for determining the necessity of factory planning measures in case a new product variant is introduced to the factory. It supports the development of different factory configurations for the evaluation of the factory life cycle, so that the total costs and environmental impacts resulting from a new product variant in a factory are known prior to its introduction. Ultimately, the different configuration variants serve as a calculation basis for sales for a more transparent decision on the introduction of a new product variant.

**Keywords:** Factory planning · Variant management · Life cycle evaluation

## 1 Introduction

"You can have any color you want as long as it is black" [1]. This statement by Henry Ford reflects that in 1912 a seller's market prevailed. Nowadays, oversupply of goods allows buyers to choose from a variety of products [2]. Companies must increasingly differentiate their products from those of their competitors and respond more intensively to the diverse and individual wishes and needs of their customers in order to sell their products. [3] Companies assume that an expanded product portfolio particularly has a
positive impact on customer satisfaction and that an increase in revenue can be realized through increased sales or higher prices [4]. Even if these strategies may be promising, they generate additional effort and costs during implementation [5]. These costs hardly ever occur completely where they were caused: 50-80% of variant-driven costs occur in production and logistics [3]. After all, the complexity of internal production and logistics processes increases with growing product differentiation [6]. Companies often systematically underestimate the additional costs, so that they end up in a cost trap [7]. This is because attempts to reduce complexity or excess capacity cannot reduce the associated costs and environmental impacts to the same extent [8]. The individualization of products is only justifiable if the customer is willing to bear the costs of the increasing complexity. Otherwise, companies are risking the economic but also the environmental sustainability of their factories and thus their competitiveness in the long term. Therefore, potential variant-driven costs and environmental impacts on the factory must be estimated in advance so that they can be discussed controversially with sales and development before the introduction of a new product or variant [2]. In the following, an approach for the systematic determination of the necessity and derivation of factory planning measures in the case of the introduction of a new product variant is developed, in order to be able to work out different factory configurations, whose economic and ecological sustainability can be evaluated using an envisioned prognosis model of the factory life cycle.

## 2 The Role of Factory Planning in Variant Management

Each individual product within a product family is referred to as a product variant. While the product family of a model targets a specific market segment, the product variants are developed to meet a specific subset of identified customer needs [9]. All product families combined form the cross-model production portfolio. The variance from successor to predecessor model is referred to as product sequence. The product variants are specified in the product structure, which displays the variants among the components and modules of a model. The variant diversity thus results from the variant parts. [10] It is generally increasing due to higher customer expectations in terms of functionality and quality as part of the ongoing trend toward individualization [5]. Other factors can be technology-driven or have a social or technical origin [11]. When introducing a new product variant to an existing factory, three scenarios can be distinguished [12]:

* **Integration:** The new product variant is integrated in the existing production

* **Substitution:** The new product variant replaces the older product in the existing production

* **Adaptation:** The new product variant cannot be integrated and is manufactured in a separate production facility

Based on this, the types of factory planning - development planning, replanning, demolition or revitalization- and the scope of a factory planning project to be initiated can be derived [13]. Factory planning designs personnel, technical-organizational processes as well as their elements and structures and provides the solution space for factory
operation [14]. Factory operation runs, manages and controls the processes in the factory in order to ensure target alignment through the interaction of people, technology and organization as well as cooperation within and outside the factory [15]. The factory targets to be achieved in planning and operation are derived from the company targets [14]. So far, profitability of a factory has been regarded as a meta-target so that competitive products can be produced [16]. In light of the climate change and limited resources, factories increasingly have to include environmental sustainability in their target system [17]. The planning and operation of a factory represent two essential phases of the factory life cycle for meeting set factory targets. A large portion of the costs and environmental impacts are determined during factory planning, but they do not occur until operation as a later phase. Since factory operation can last up to several decades, most costs and environmental impacts occur at this point, making it the most relevant life cycle phase from an economic and environmental perspective [18]. Therefore, life cycle-oriented factory planning deliberately includes the operation phase in the decision-making process for the selection of a specific factory configuration. By evaluating how the planned factory configuration copes with uncertainties during factory operation, economic and environmental sustainability is ensured over the considered lifetime of a factory [19].

Due to internal and external change drivers, it is often not possible to avoid a fundamental diversity of variants, so that variant-driven expenses inevitably emerge in factory operation. The different economic aspects have been summarized in Fig. 1 showing that the perceived customer benefit and the associated revenue follows a degressive trend, while the prevailing complexity costs are progressive, so that profit decreases and no value can be created beyond a certain number of variants.

<figure><img src="image_3.png" /><figcaption>Fig. 1. Economic aspects [4, 7, 8, 20] resulting from an increasing number of product variants whose complexity can be controlled preventively (black) or reduced reactively (blue)</figcaption></figure>

In the literature, variant-driven expenses are also referred to as complexity costs for coping with increased complexity [21]. Expected economies of scale are overestimated
when introducing more variants. On the contrary, diseconomies of scope arise, partic-
ularly in indirect fields such as logistics, which do not become apparent immediately
[4, 22]. The basic task of variant management is to manage the increasing number of
product variants caused by diversification and the resulting complexity [23]. In contrast,
complexity management does not focus on the product, but analyzes the complexity
generated within the overall system [4]. The strategies of variant management are dis-
tinguished into complexity reduction, complexity control and complexity avoidance. In
complexity reduction, unprofitable variants are removed from the portfolio. Complexity
control aims at providing the diversity of variants requested by the customer at low cost
[23]. When trying to reduce the variety, or the complexity in general, the investments
made and the associated environmental impacts cannot be reduced to the same extent.
This asymmetric-dynamic cost behavior is also called cost remanence. Fixed costs which
are not reducible or only reducible in the long term are called hysteresis effect or cost trap
in this context [4, 8] Furthermore, excess capacities can arise from a previous capacity
expansion in addition to cost remanence. The resulting costs for unused capacities are
called cost recurrence [4].

The challenge of the cost trap lies in the perception of imminent variant diversity, which increases as product development progresses. At the same time the ability of interference decreases rapidly. Thus, implementation of variants can lead to missed factory targets. However, subsequent attempts to reduce the number of variants is less cost-effective (dashed line). Therefore it is necessary to implement complexity control and to evaluate the impact of variant management measures on the sustainability of the factory at an early stage of product development [20].

3 Challenges of Evaluating the Impact of New Product Variants

An overview of different approaches can be found in the literature review by ELMARAGHY ET AL. on the effective co-development of variants and their manufacturing systems to ensure economic sustainability [24]. The approaches most relevant to this paper are discussed in the following.

In order to make the variants controllable and to create transparency for variant
management, SCHUH has developed the variant tree [25]. This can be used to illustrate
the diversity across the stages of an assembly process [4]. Based on this, the Variant
Mode and Effect Analysis (VMEA) systematically presents variant information and
thus supports product planning and design along the value chain [26].

BAYER has developed variant costing using complexity factors to identify the busi-
ness areas most affected by variant diversity [27]. A process analysis with subsequent
variant cost calculation is based on product-related factors in order to identify business
units affected by variant diversity the most.

A methodical approach for determining variant-induced costs was developed by BIEDERMANN with the goal of achieving simple implementation in a short time [5]. Complexity costs of reference variants of variant groups are calculated and presented as a variant tree in order to support decision making. BROSCH presents a similar approach with the "Design for Value Chain" methodology (DfVC) using complexity drivers [28].

An approach presented by NEMC (next evolution Management Consulting GmbH) aims to identify variant-driven costs directly in the product development process along
the value chain. However, a decision to introduce a product variant has already been made and represents the starting point [6].

Overall, approaches for evaluating the impact of product variants mainly focus on the market cycle and less on the phase before market launch. However, in order to manage complexity in the best possible way, critical aspects must already be taken into account before the planning process is completed. This includes necessary adjustments of the factory configuration to facilitate the production of the product variant. Only if the necessary adjustments and the resulting consequences for factory operation are evaluated during product planning, a cost trap can be avoided and complexity can be successfully controlled. It is therefore necessary to forecast the impact of a new product variant on the economic and environmental sustainability of the factory over the entire product life cycle. Thus, variants are not subsequently reduced but deliberately increased, if factory sustainability is not compromised. Otherwise, a distinction between value-creating and value-destroying variant-induced complexity is not made.

# 4 Approach for Deriving Factory Planning Measures for the Life Cycle-Oriented Evaluation of New Product Variants

The basic principle of life cycle-oriented factory planning, namely the anticipation of the use phase of a factory with its trends but also possible disruptions for an early consideration during the planning of a factory configuration, addresses precisely the challenges of variant management described above. Emphasis is put on the timely evaluation of costs and environmental impacts in factory operation, which account for a significant share of the complexity expenses. Thus, impacts of new product variants can be predicted or possible future variant scenarios can be thought through and a target value for the number of variants can be set. This provides variant management with complete transparency at the time of decision-making, so that cost remanence is avoided in the best possible way and both the economic and environmental sustainability of a factory can be ensured. The concept of factory life cycle evaluation has already been described in detail [19]. However, the focus has not been on the systematic planning and generation of factory configurations in line with requirements. This is the final missing element of life cycle-oriented factory planning. But the derivation of factory planning measures is very case- and problem-specific, so that the approach visualized in Fig. 2 concentrates on handling new product variants. The impacts of new product variants on the factory are based on the interdependencies of a product with the factory. They cannot be determined in general but rather depend on specific product features and attributes of the elements to be designed in a factory. This is because a factory is also referred to as a socio-technical system, which cannot be designed as a stand-alone planning element [16]. WULF offers a possible classification of product features [12]. For example, physical properties are tangible attributes such as the dimension or weight of a product. Based on the interdependencies of the individual product features with the factory elements, the identified relationships as change dimensions can be described in more detail. For instance, the physical properties of a product show direct dependencies with the technical factory elements. Thus, if there is a physical change in the product, it may have an impact on the storage, transportation or production facilities.
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Approach for Deriving Factory Planning Measures for the Life Cycle-Oriented Evaluation of New Product Variants.</figcaption></figure>

The relevance of the individual change dimensions for factory planning in a specific use case can be determined by analyzing the predominant conditions in a factory. For this purpose, mathematical functions are formulated to analyze the current state of a factory element using inherent attributes and attributes of interdependent factory elements. These functions represent an entry condition for associated cause-effect diagrams in order to investigate, why a particular factory element does not meet the new requirements of a changed product feature (e.g. load-bearing capacity of a storage location for handling a higher weight of a product, while also taking into account load carriers, stock level etc.). This generates an understanding of how certain attributes contribute to the ability of a factory element to cope with the changed requirements and provides the basis for deriving specific factory planning measures in order to upgrade the according factory element. Provided that certain measures are selected to generate a factory configuration variant, further indirect interdependencies between factory elements must be considered, since factory planning decisions in one area of the factory can have a significant impact on another area of the factory (e.g. new shelf bay causes additional spatial demand). For factory elements indirectly impacted by a changed product feature, further mathematical change dimensions can be formulated and cause-effect diagrams established based on the inducing attribute. Once all interdependencies have been considered for a factory configuration and further factory configurations have been developed by deriving alternative factory planning measures, the factory configurations can be evaluated using the
envisioned prognosis model of the factory life cycle. The proportional costs and envi-
ronmental impacts determined in this way over the expected product life cycle can be
further used as a calculation basis by sales in the context of variant management.

5 Summary and Outlook

Generally, an increase in revenue due to higher sales is expected to outweigh possible
negative effects caused by a new product variant. But the complexity resulting from
a high number of variants can quickly exceed the limit of controllability in a factory.
Therefore, the ability to control complexity is regarded as a strategic success factor
of a company. In order to realize variant control, it is necessary to evaluate measures
taken in variant management regarding their impact on the sustainability of the factory
at an early stage of product development. However, this transparency about the cost
structure of the factory as a significant cost driver is usually not available to sales. After
all, a strategy shift from variant reduction to variant control requires a forecast of the
impacts of possible decisions on the factory and its operation. The adequate approach
of life cycle-oriented factory planning is currently still under development. Based on
the concept of factory life cycle evaluation, an approach has been developed for the
systematic and requirement-based derivation of factory planning measures for coping
with new product variants in the factory. So far, it is still in a conceptual phase and
has not yet been combined with the evaluation model. An exemplary application is not
possible yet. When implementing the approach, a consistent level of detail as well as
a certain generality of the cause-effect diagrams will represent the greatest challenges.
Future research will be necessary on the allocation of total costs and the relevance of
environmental impacts in product cost accounting.

**Acknowledgments.** Partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—412409961. The authors wish to thank Antal Dér and Christoph Herrmann for the valuable discussions.

References

1. Duncan, J.L.: Any colour—so long as it’s black: designing the model t ford 1906–1908. Exisle Pub, Wollombi (2008)

2. Maune, G.: Möglichkeiten des Komplexitätsmanagements für Automobilhersteller auf Basis durchgehender IT-gestützter System (2002)

3. Fischer, J.O.: Kostenbewusstes Konstruieren. Springer, Berlin, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78313-8

4. Schuh, G., Riesener, M.: Produktkomplexität managen: Strategien - Methoden - Tools, 3rd edn. Hanser, München (2017)

5. Biedermann, H.: Industrial Engineering and Management. Springer, Wiesbaden (2016)

6. Keuper, F., Schomann, M.: Management von IT und IT-gestütztes Management, 1st edn. Gabler Verlag, Wiesbaden (2008)

7. Albers, S. (ed.): Strategieentwicklung - Produktplanung - Organisation - Kontrolle, 3rd edn. Gabler, Wiesbaden (2007)
8. Hichert, R.: Probleme der Vielfalt. Teil 1: Soll man auf Exoten verzichten? Werkstattstechnik, wt - Zeitschrift fuer Industrielle Fertigung 75, 235-237 (1985)

9. Romero, F., Sanfilippo, E.M., Rosado, P., Borgo, S., Benavent, S.: Feature in product engineering with single and variant design approaches. a comparative review

10. Wiendahl, H.-P., Gerst, D., Keunecke, L. (eds.): Variantenbeherrschung in der Montage. Konzept und Praxis der flexiblen Produktionsendstufe. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-642-18947-0

11. Schuh, G.: Produktkomplexität managen: Strategien; Methoden; Tools, 1st edn. Carl Hanser Fachbuchverlag, s.l. (2014)

12. Wulf, S., Bewertung des Einflusses von Produkt- und Technologieveränderungen auf die Fabrik. Dissertation, Hannover (2011)

13. Verein Deutscher Ingenieure. Factory planning Planning procedures: VDI 5200 (2011)

14. Wiendahl, H.-P., Reichardt, J., Nyhuis, P.: Handbook Factory Planning and Design, 2015th ed., Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46391-8

15. Schenk, M., Wirth, S., Müller, E.: Factory Planning Manual: Situation-Driven Production Facility Planning, 2010th edn. Springer, Berlin (2014)

16. Nyhuis, P., Heger, C.L.: Adequate factory transformability at low costs. In: International Conference on Competitive Manufacturing (COMA) (2004)

17. Kadner, S., Kobus, J., Stuchtey, M.R., Weber, T.: Circular economy roadmap für deutschland. acatech Studie, R. acatech/SYSTEMIQ, München/London (2021)

18. Gebler, M., Cerdas, J.F., Thiede, S., Herrmann, C.: Life cycle assessment of an automotive factory: Identifying challenges for the decarbonization of automotive production – a case study. J. Clean Prod. 270 (2020)

19. Dér, A., Hingst, L., Nyhuis, P., Herrmann, C.: A review of frameworks, methods and models for the evaluation and engineering of factory life cycles. Advances in Industrial and Manufacturing Engineering (under revision) (2022)

20. Lindemann, U., Reichwald, R., Zäh, M.F.: Individualisierte Produkte - Komplexität beherrschen in Entwicklung und Produktion. Springer-Verlag, Heidelberg (2006). https://doi.org/10.1007/3-540-34274-5

21. Ehrlenspiel, K.: Kostengünstig Entwickeln und Konstruieren: Kostenmanagement Bei der Integrierten Produktentwicklung, 8th edn. Springer, Heidelberg (2020). https://doi.org/10.1007/978-3-642-41959-1

22. Kestel, R.: Variantenvielfalt und Logistiksysteme: Ursachen - Auswirkungen - Lösungen. Deutscher Universitätsverlag, Wiesbaden (1995)

23. Wildemann, H.: Variantenmanagement: Leitfaden zur Komplexitätsreduzierung, -beherrschung und -vermeidung, 26th edn. TCW-Verlag, München (2018)

24. ElMaraghy, H., Schuh, G., ElMaraghy, W., Piller, F., Schönsleben, P., Tseng, M., Bernard, A.: Product variety management. Manufacturing Technology, 629-652 (2013)

25. Schuh, G.: Gestaltung und Bewertung von Produktvarianten ein Beitrag zur Systematischen Planung von Serienprodukten. Dissertation, VDI-Verl., Aachen (1989)

26. Caesar, C.: Kostenorientierte Gestaltungsmethodik für Variantenreiche Serienprodukte: Variant Mode and Effects Analysis (VMEA). Dissertation, VDI-Verl., Aachen (1991)

27. Bayer, T.: Variantenkostenbewertung mit faktorenanalytischen Komplexitätstreibern. Zugl.: Karlsruhe, Univ., Diss., 2010, 1st ed., Hampp, München (2010)

28. Brosch, M.: Eine Methode zur Reduzierung der produktvarianteninduzierten Komplexität. Dissertation, Techn. Univ. Hamburg-Harburg Univ.-Bibl, Hamburg (2014)