A Stackelberg game theoretic model for optimizing product family architecting with supply chain consideration

Planning of an optimal product family architecture (PFA) plays a critical role in defining an organization's product platforms for product variant configuration while leveraging commonality and variety. The focus of PFA planning has been traditionally limited to the product design stage, yet with limited consideration of the downstream supply chain-related issues. Decisions of supply chain configuration have a profound impact on not only the end cost of product family fulfillment, but also how to design the architecture of module configuration within a product family. It is imperative for product family architecting to be optimized in conjunction with supply chain configuration decisions. This paper formulates joint optimization of PFA planning and supply chain configuration as a Stackelberg game. A nonlinear, mixed integer bilevel programming model is developed to deal with the leader–follower game decisions between product family architecting and supply chain configuration. The PFA decision making is represented as an upper-level optimization problem for optimal selection of the base modules and compound modules. A lower-level optimization problem copes with supply chain decisions in accordance with the upper-level decisions of product variant configuration. Consistent with the bilevel optimization model, a nested genetic algorithm is developed to derive near optimal solutions for PFA and the corresponding supply chain network. A case study of joint PFA and supply chain decisions for power transformers is reported to demonstrate the feasibility and potential of the proposed Stackelberg game theoretic joint optimization of PFA and supply chain decisions

Bi-objective optimization for low-carbon product family design

[EN] Consumers, industry, and government entities are becoming increasingly concerned about the issue of global warming. With this in mind, manufacturers have begun to develop products with consideration of low-carbon. In recent years, many companies are utilizing product families to satisfy various customer needs with lower costs. However, little research has been conducted on the development of a product family that considers environmental factors. In this paper, a low-carbon product family design that integrates environmental concerns is proposed. To this end, a new method of platform planning is investigated with considerations of cost and greenhouse gas (GHG) emission of a product family simultaneously. In this research, a lowcarbon product family design problem is described at first, and then a GHG emission model of product family is established. Furthermore, to support lowcarbon product family design, an optimization method is applied to make a significant trade-off between cost and GHG emission to implement a feasible platform planning. Finally, the effectiveness of the proposed method is illustrated through a case study. (C) 2016 Elsevier Ltd. All rights reserved.This research was carried out as a part of the CASES project which is supported by a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Programme under the Grant agreement no. 294931. This research was also supported by National Natural Science Foundation of China (Nos. 51175262, 51575264); and Jiangsu Province Science Foundation for Excellent Youths under Grant BK2012032.Wang, Q.; Dunbing, T.; Yin, L.; Salido, MA.; Giret Boggino, AS.; Xu, Y. (2016). Bi-objective optimization for low-carbon product family design. Robotics and Computer-Integrated Manufacturing. 41:53-65. https://doi.org/10.1016/j.rcim.2016.02.001S53654

모듈러 제품군 운영을 위한 다양성 관리 방법론

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 산업공학과, 2021. 2. 홍유석.글로벌 제조업체들은 다양한 제품을 출시하기 위해 모듈러 디자인 전략을 제품개발에 적용해왔다. 모듈러 디자인 전략은 제품을 모듈 단위로 구분한 후, 여러 종류의 모듈을 조합하여 새로운 제품을 만드는 전략이다. 모듈러 디자인은 제조업체가 제품다양성을 달성할 수 있도록 하였지만, 제공하는 제품의 수가 무수히 많아지면서 제품다양성으로 인한 안 좋은 영향들이 설계 영역뿐만 아니라, 시장, 생산 영역에서 지속적으로 발생하고 있는 실정이다. 따라서, 본 논문에서는 제품다양성의 안 좋은 영향을 줄일 수 있도록 이를 체계적으로 개발하고 운영하는 다양성 관리(variety management) 방법론을 제안한다. 다양성 관리를 성공적으로 수행하기 위해서는 교차영역 관점과 변종 수준 관점의 접근이 필요하다. 교차영역 관점은 제품다양성이 영향을 미치는 시장, 설계, 생산 영역의 요소들의 연결관계를 정립하는 메커니즘을 제공하며, 변종 수준 관점은 일반적인 요소(elements) 수준에서 한 단계 내려가 다양성 관리에 실제 문제가 되는 각 요소들의 변종들(variants)을 체계적으로 관리할 수 있도록 한다. 이 두 가지 관점에서, 본 논문은 다양성 관리에서 중요하게 다루어야 할 세 가지 과제–예상치 못한 변종의 발생 방지, 설계 복잡성 감축, 시장 점유율과 복잡성 비용 사이의 균형 잡기–를 해결하기 위한 방법론을 제안한다. 첫 번째 주제에서는, 아키텍처 기반의 접근법을 활용한 변종 관리 아키텍처(VA, variation architecture)를 도입하여 예상치 못한 변종의 발생을 방지하고자 한다. 개발 아키텍처는 모듈러 제품군을 개발할 때 사용하는 일종의 참조 아키텍처로, 시장 속성, 설계 모듈, 생산 설비의 연결관계를 정의하는 교차영역 연결 메커니즘을 제공한다. 변종 관리 아키텍처에서는 일반 수준의 계획과 변종 수준의 계획을 함께 세울 수 있다. 일반 수준에서는 요소 간 연결관계의 종류를 정의하여 제품군의 다양성 수준을 결정하고, 변종 수준에서는 변종들 간의 조합 규칙을 설정하여 불필요한 변종의 발생을 최소화한다. 또한, 본 연구에서는 제조업체가 변종 관리 아키텍처를 활용할 수 있도록 아키텍처 구축 프레임워크를 제안한다. 사례 연구에서는 자동차 프론트섀시 제품군을 통해 제품 및 변종의 수를 상당히 줄일 수 있음을 보여 줌으로써 프레임워크의 실용성을 검증한다. 다음으로, 인터페이스 표준화 개념을 적용하여 변종들 간의 복잡한 관계로부터 발생하는 설계 복잡성을 줄이는 연구를 수행한다. 본 연구에서 제안하는 인터페이스 설계 방법론은 하나가 아닌 다수의 표준 인터페이스를 사용하도록 허용한다. 모듈 변종들을 연결하기 위해 다수의 인터페이스를 도입하면, 인터페이스의 수와 적용범위에 따라 모듈러 제품군의 전체 구조가 달라지고 설계 복잡성 또한 다양한 양상으로 발생한다. 이를 측정하기 위해, 본 연구에서는 인터페이스의 선택에 영향을 받는 두 가지 복잡성 지표를–인터페이스 표준화 복잡성과 통합 복잡성을–정의한다. 인터페이스 표준화 복잡성은 표준 인터페이스를 설계할 때, 모듈 변종 설계자 간의 조율에 필요한 맨아워(person-hour)를 계산하고, 통합 복잡성은 각각의 모듈 변종과 인터페이스를 통합된 제품으로 설계하는데 필요로 하는 노력의 양으로, 위상적 복잡성(topological complexity) 지표를 기반으로 측정한다. 본 연구에서는 두 가지 복잡성을 최소화하는 인터페이스 설계 대안을 찾기 위한 프레임워크를 제공한다. 사례 연구에서 이의 적용성을 보여주기 위해 프론트섀시 제품군에 맞는 최적의 인터페이스 수와 제품군 구조를 도출한다. 마지막 주제에서는, 시장 점유율과 복잡성 비용의 균형을 맞추는 최적 제품 종수를 찾기 위한 최적화 모델을 개발한다. 최적화 모델은 제품을 구성하는 모듈 변종을 기반으로 모델링되고, 제품 및 모듈 종수가 증가함에 따라 시장 점유율의 증가분이 줄어들고, 반대로 복잡성 비용의 증가분은 늘어나는 특성을 반영한다. 시장 점유율을 구하기 위해 네스티드 로짓 모델(nested logit model)을 기반으로 하는 수요 모델을 개발한다. 네스티드 로짓 모델에서는 동일 제품군 내 제품들의 유사성을 고려하여 시장 점유율의 증가분이 줄어드는 특성을 반영한다. 다음으로, 제로베이스 원가계산 접근법(zero-based costing approach)을 활용한 복잡성 비용 모델을 도입한다. 이 접근법에서는 제품 혹은 모듈의 종수가 한 단위씩 늘어날 때 발생하는 비용을 단계적으로 계산하는 방법을 사용한다. 마지막으로, 수요 모델과 복잡성 비용 모델을 합친 최적화 모델(optimization model)을 모델링하여 최적 제품 종수와 제품의 모듈 구성을 도출하는 연구를 수행한다. 사례 연구에서는 민감도 분석을 수행하여 각 상황별 최적해가 어떻게 달라지는 지 보여주어 연구에서 제안하는 모델들의 효과를 검증한다.Global manufacturing companies have been achieving product variety by implementing a modular design strategy in which product variants are created by combining, adding, or substituting modules. Providing a high variety of products, however, causes negative effects not only on design but also on market and production. Variety management that defines the right range of variants is one of the most critical issues for most of the manufacturing companies. This thesis aims to propose methodologies that enable companies to systematically reduce negative effects of variety. In order to achieve successful variety management, this study approaches the issue from two viewpoints: cross-domain and variant-level viewpoints. A cross-domain viewpoint supports establishing relationships between elements in market, design, and production domain that are affected by product variety, and a variant-level viewpoint enables to explicitly manage variants of elements that are the main source of negative effects. In these viewpoints, this thesis focuses on dealing with three important challenges in variety management: to prevent unexpected variants, to reduce design complexity, and to balance market share and complexity cost. In the first theme, an architecture-based approach named variation architecture is introduced to prevent unexpected variants. Variation architecture (VA) is defined as a reference architecture for a modular product family providing the scheme by which variants in market, design, and production domain are arranged by cross-domain mapping mechanisms. The VA consists of generic-level and variant-level plans. At the generic-level, mapping types between domain elements are determined, and at the variant-level, combination rules between variants are set to reduce unexpected variants. Then, a framework is proposed to increase the practicality of the VA so that its compositions are well defined. In the case study, the framework is applied to an automobile front chassis family. The result shows that the number of module variants is significantly reduced compared to the current number of variants in operation. Secondly, the concept of interface standardization is introduced to manage design complexity caused by complicated combinations between module variants. This theme proposes an interface design methodology that addresses multiple standard interfaces in a modular product family. A product family structure is changed by implementing multiple standard interfaces, generating design complexity. This study defines two complexities resulting from the introduction of multiple standard interfaces: standardization effort and integration effort. Standardization effort is estimated as a required person-hours for coordinating module variants to design a standard interface, and integration effort is measured as an effort to integrate all design elements based on the concept of topological complexity. A framework is proposed to identify an optimal product family structure that minimizes the two complexities. In the case study, the proposed framework identifies an optimal structure and the number of standard interfaces for the front chassis family. Then, the study conducts a sensitivity analysis to demonstrate the methodologys applicability in interface management. In the last theme, an optimization model is developed to identify an optimal product variety to balance market share and complexity cost. The model focuses on module variants, not just product variants, because a modular product family creates product variants by combining module variants. The model reflects the trends of concave increase in market share and convex increase in complexity cost as the number of variety increases. A demand model is developed by the nested logit model that shows the concavity of market share based on the similarity of product variants in the same family, and a complexity cost model is constructed by the zero-based costing approach that an incremental cost is estimated as a variant is added. Combining the models, an optimization model is formulated to find an optimal variety and configurations of product variants. The case study demonstrates the models effectiveness by analyzing optimal solutions in various situations.Abstract i Contents iv List of Tables viii List of Figures ix Chapter 1 Introduction 1 1.1 Variety Management 1 1.2 Variety Management Challenges 5 1.3 Research Proposal: How to Deal with the Challenges? 7 1.4 Structure of Thesis 10 Chapter 2 Literature Review 11 2.1 Variety Management Methodologies 11 2.1.1 Modular product family design 11 2.1.2 Product family architecture 13 2.1.3 Classification of the contributions 15 2.2 Modular Design and Complexity 17 2.2.1 Modular design 17 2.2.2 Interface design 19 2.2.3 Design complexity 20 2.3 Product Family Design and Variety 22 2.3.1 Product family design 22 2.3.2 Variety optimization 25 Chapter 3 Variation Architecture for Reducing the Generation of Unexpected Variants 29 3.1 Introduction 29 3.1.1 Generation of unexpected variants 29 3.1.2 Needs for a systematic approach 31 3.2 Variation Architecture (VA) 33 3.2.1 Generic-level planning 34 3.2.2 Variant-level planning 41 3.3 Framework for Planning Product Variety 46 3.4 Application 47 3.4.1 Case description 47 3.4.2 Construction of variation architecture (VA) 49 3.4.3 Result and discussion 53 3.5 Summary 57 Chapter 4 Variant-level Interface Design for Reducing Design Complexity 59 4.1 Introduction 59 4.2 Variant-level Interface Design 61 4.3 Interface Design Complexity 64 4.3.1 Standardization effort 66 4.3.2 Integration effort 71 4.4 Framework for Variant-level Interface Design 76 4.5 Case Study 79 4.5.1 Application of the framework 79 4.5.2 Analysis and discussion 84 4.6 Summary 88 Chapter 5 Optimizing Product Variety for Balancing Market Share and Complexity Cost 91 5.1 Introduction 91 5.2 Evidence of the impact of variety on market share 94 5.3 Planning of Product Configurations 96 5.3.1 Product family architecture 96 5.3.2 Product configuration 98 5.4 Variety Optimization Model 100 5.4.1 Demand model 100 5.4.2 Complexity cost model 104 5.4.3 Optimization model 108 5.5 Case Study 110 5.5.1 Case description 110 5.5.2 Data source 112 5.5.3 Optimization setting 113 5.5.4 Result 115 5.5.5 Discussion 118 5.6 Summary 122 Chapter 6 Conclusion 125 6.1 Summary of Contributions 125 6.2 Limitations and Future Research Directions 127 Bibliography 129 Appendix A Variant-level Plan of a Front Chassis Family 147 Appendix B Adjacency and Combination Matrices of a Front Chassis Family 151 국문초록 155Docto

Modularity Analysis and Commonality Optimization for the Top-down Platform-Based Product Family Design

Ph.DDOCTOR OF PHILOSOPH

Concurrent Product and Supply Chain Architecture Design Considering Modularity and Sustainability

Since sustainability is a growing concern, businesses aim to integrate sustainability principles and practices into product and supply chain (SC) architecture (SCA) design. Modular product architecture (MPA) is essential for meeting sustainability demands, as it defines detachable modules by selecting appropriate components from various potential combinations. However, the prevailing practice of MPA emphasizes architectural aspects over interface complexity and design production processes for the structural dimension, potentially impending manufacturing, assembly/disassembly, and recovery efficiency. Most MPA has been developed assuming equal and/or fixed relations among modules rather than configuring for SC effectiveness. Therefore, such methods cannot offer guidance on modular granularity and its impact on product and SCA sustainability. Additionally, there is no comparative assessment of MPA to determine whether the components within the configured modules could share multiple facilities to achieve economic benefits and be effective for modular manufacture and upgrade. Therefore, existing modular configuration fails to link modularization drivers and metrics with SCA, hampering economic design, modular recycling, and efficient assembly/disassembly for enhancing sustainability. This study focuses on the study of design fundamentals and implementation of sustainable modular drivers in coordination with SCA by developing a mathematical model. Here, the architectural and interface relations between components are quantified and captured in a decision structure matrix which acts as the foundation of modular clustering for MPA. Again, unlike previous design approaches focused only on cost, the proposed work considers facility sharing through a competitive analysis of commonality and cost. It also evaluates MPA's ease of disassembly and upgradeability by a comparative assessment of different MPA to enhance SCA sustainability. The primary focus is concurrently managing the interdependency between MPA and SCA by developing mathematical models. Consistent with the mathematical model, this thesis also proposes better solution approaches. In summary, the proposed methods provide a foundation for modeling the link between product design and SC to 1) demonstrate how sustainable modular drivers affect the sustainability performance, 2) evaluate the contribution of modularity to the reduction of assembly/disassembly complexity and cost, 3) develop MPA in coordination with SC modularity by trading off modular granularity, commonality, and cost, and 4) identify a sustainable product family for combined modularity considering the similarity of operations, ease of disassembly and upgradability in SCA. Using metaheuristic algorithms, case studies on refrigerators showed that MPA and its methodology profoundly impact SCA sustainability. It reveals that interactions between components with levels based on sustainable modular drivers should be linked with modular granularity for SCA sustainability. Another key takeaway is that instead of solely focusing on cost, facility sharing and ensuring ease of disassembly and upgradeability can help to reap sustainability benefits

A multi-agent optimisation model for solving supply network configuration problems

Supply chain literature highlights the increasing importance of effective supply network configuration decisions that take into account such realities as market turbulence and demand volatility, as well as ever-expanding global production networks. These realities have been extensively discussed in the supply network literature under the structural (i.e., physical characteristics), spatial (i.e., geographical positions), and temporal (i.e., changing supply network conditions) dimensions. Supply network configuration decisions that account for these contingencies are expected to meet the evolving needs of consumers while delivering better outcomes for all parties involved and enhancing supply network performance against the key metrics of efficiency, speed and responsiveness. However, making supply network configuration decisions in the situations described above is an ongoing challenge. Taking a systems perspective, supply networks are typically viewed as socio-technical systems where SN entities (e.g., suppliers, manufacturers) are autonomous individuals with distinct goals, practices and policies, physically inter-connected transferring goods (e.g., raw materials, finished products), as well as socially connected with formal and informal interactions and information sharing. Since the structure and behaviour of such social and technical sub-systems of a supply network, as well as the interactions between those subsystems, determine the overall behaviour of the supply network, both systems should be considered in analysing the overall system

THE EFFECT OF PRODUCT DESIGN MODULARITY ON SUSTAINABLE SUPPLY CHAIN MANAGEMENT

This thesis integrates between three major fields of study: product design, supply chain management and sustainability. This thesis introduces product design modularity (PDM) as a product design methodology and evaluates its influence on supply chain operations. This is done with a view to assess whether adopting modularity in design enhances a supply chain’s economic, environmental and social performance. The research conducted within this thesis follows a pragmatic philosophy with the focus being on the research questions instead of on the type of data available. Abductive reasoning is used to collect and present quantitative and qualitative data to answer whether modularity in design leads to more sustainable supply chain operations. A conceptual framework integrating PDM and sustainable supply chain management (SSCM) is developed within the thesis. The conceptual framework presents all supply chain processes affected by product design.The framework further differentiates these effects into economic, environmental, or social categories depending on which aspect of sustainability is impacted by PDM. The research implements a case study strategy. The case study focuses on a washing machines product family for a well-known white goods electronics manufacturer in Egypt. The case study follows a comparative approach, where the analysis is structured around assessing the effects modules with differing designs (one has a modular design and the other has an integral design) have on the economic, environmental and social performance of a supply chain. To assess the effect of PDM on SSCM analytical hierarchy processing (AHP) has been used. The hierarchy focuses on presenting a holistic view to sustainability by considering economic, environmental, and social supply chain aspects simultaneously. Supply chain processes influenced by product design modularity make up the criteria within the hierarchy. The model develops pairwise comparisons that assess the effect modular versus integral components have on the sustainability of supply chain operations within the case study. Data collected and analysed within the case provided that the modular component led to improved economic, environmental and social performance when compared to the integral component. This research presents PDM as a viable solution, which supply chains can adopt to become more sustainable. The integration of product design and supply chain design allows for the decision making process to be sufficiently flexible to overcome the common barriers supply chains face when attempting to implement sustainable procedures. This research offers a guide to assist supply chains improve their sustainability through providing a cause and effect relationship linking product design decisions to a supply chain’s economic, environmental and social performance. In turn this allows companies to include sustainability considerations and have more control on the sustainability of their operations from the product design stage. From an academic perspective, assessing the effect different product design approaches (modular versus integral) have on the sustainability of supply chain operations offers tangible solutions for improving SSCM. The conceptual framework presented an integrated review for all supply chain processes affected by product design. Furthermore, the framework classifies these processes depending on which aspect of sustainability they affect. From a practical perspective, the AHP model developed provides an analytical tool to assist product designers in choosing the best product design alternatives to improve sustainability within a supply chain

Integrating Human Performance Models into Early Design Stages to Support Accessibility

Humans have heterogeneous physical and cognitive capabilities. Engineers must cater to this heterogeneity to minimize opportunities for user error and system failure. Human factors considerations are typically evaluated late in the design process, risking expensive redesign when new human concerns become apparent. Evaluating user capability earlier could mitigate this risk. One critical early-stage design decision is function allocation – assigning system functions to humans and machines. Automating functions can eliminate the need for users to perform risky tasks but increases resource requirements. Engineers require guidance to evaluate and optimize function allocation that acknowledges the trade-offs between user accommodation and system complexity. In this dissertation, a multi-stage design methodology is proposed to facilitate the efficient allocation of system functions to humans and machines in heterogeneous user populations. The first stage of the methodology introduces a process to model population user groups to guide product customization. User characteristics that drive performance of generalized product interaction tasks are identified and corresponding variables from a national population database are clustered. In stage two, expert elicitation is proposed as a cost-effective means to quantify risk of user error for the user group models. Probabilistic estimates of user group performance are elicited from internal medicine physicians for generalized product interaction tasks. In the final stage, the data (user groups, performance estimations) are integrated into a multi-objective optimization model to allocate functions in a product family when considering user accommodation and system complexity. The methodology was demonstrated on a design case study involving self-management technology use by diabetes patients, a heterogeneous population in a safety-critical domain. The population modeling approach produced quantitatively and qualitatively validated clusters. For the expert elicitation, experts provided internally validated, distinct estimates for each user group-task pair. To validate the utility of the proposed method (acquired data, optimization model), engineering students (n=16) performed the function allocation task manually. Results indicated that participants were unable to allocate functions as efficiently as the model despite indicating user capability and cost were priorities. This research demonstrated that the proposed methodology can provide engineers valuable information regarding user capability and system functionality to drive accessible early-stage design decisions

A systematic approach for integrated product, materials, and design-process design

Designers are challenged to manage customer, technology, and socio-economic uncertainty causing dynamic, unquenchable demands on limited resources. In this context, increased concept flexibility, referring to a designer s ability to generate concepts, is crucial. Concept flexibility can be significantly increased through the integrated design of product and material concepts. Hence, the challenge is to leverage knowledge of material structure-property relations that significantly affect system concepts for function-based, systematic design of product and materials concepts in an integrated fashion. However, having selected an integrated product and material system concept, managing complexity in embodiment design-processes is important. Facing a complex network of decisions and evolving analysis models a designer needs the flexibility to systematically generate and evaluate embodiment design-process alternatives. In order to address these challenges and respond to the primary research question of how to increase a designer s concept and design-process flexibility to enhance product creation in the conceptual and early embodiment design phases, the primary hypothesis in this dissertation is embodied as a systematic approach for integrated product, materials and design-process design. The systematic approach consists of two components i) a function-based, systematic approach to the integrated design of product and material concepts from a systems perspective, and ii) a systematic strategy to design-process generation and selection based on a decision-centric perspective and a value-of-information-based Process Performance Indicator. The systematic approach is validated using the validation-square approach that consists of theoretical and empirical validation. Empirical validation of the framework is carried out using various examples including: i) design of a reactive material containment system, and ii) design of an optoelectronic communication system.Ph.D.Committee Chair: Allen, Janet K.; Committee Member: Aidun, Cyrus K.; Committee Member: Klein, Benjamin; Committee Member: McDowell, David L.; Committee Member: Mistree, Farrokh; Committee Member: Yoder, Douglas P