Key Metrics System for Variety Steering in Mass Customization

The main goal of this paper is to provide a key metrics system for variety steering in mass customization. We distinguish between objective and subjective customer needs. The subjective needs are the individually realized and articulated requirements, whereas the objective needs are the real ones perceived by a fictive neutral perspective. We show that variety in mass customization has to be orientated on the objective needs. In order to help mass customizers better evaluate the degree to which they can fulfill the objective needs as well as their internal complexity level, we have developed a key metrics system model. We also present a conceptual application showing how to use this model to support decision making related to the introduction or reduction of product variants.Variety Management; Complexity; Production/Operations Management

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Consumer Preferences for Mass Customization

Increasingly, firms allow consumers to mass customize their products. In this study, the authors investigate consumers’ evaluations of different mass customization configurations when asked to mass customize a product. For instance, mass customization configurations may differ in the number of modules that may be mass customized. The authors find – in the context of mass customization of personal computers – that mass customization configuration affects the product utility consumers can achieve in mass customization as well as their perception of mass customization complexity. In turn, product utility and complexity affect the utility consumers derive from using a certain mass customization configuration. More specifically, product utility has a positive, and complexity has a negative effect on mass customization configuration utility. The effect of complexity is direct as well as indirect, because complexity also lowers product utility. The authors also find that consumers with high product expertise find mass customization configurations less complex than consumers with low product expertise and that for more expert consumers complexity has a less negative impact on product utility. The study has important managerial implications for how companies can design their mass customization configuration to increase utility and decrease complexity.marketing ;

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

High-level synthesis optimization for blocked floating-point matrix multiplication

In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and efficient architectures as well as detailed performance models have been developed. By design these IP cores take a fixed footprint which not necessarily optimizes the use of all available resources. Moreover, the low-level architectures are not easily amenable to a parameterized synthesis. In this paper high-level synthesis is used to fine-tune the configuration parameters in order to achieve the highest performance with maximal resource utilization. An\ exploration strategy is presented to optimize the use of critical resources (DSPs, memory) for any given FPGA. To account for the limited memory size on the FPGA, a block-oriented matrix multiplication is organized such that the block summation is done on the CPU while the block multiplication occurs on the logic fabric simultaneously. The communication overhead between the CPU and the FPGA is minimized by streaming the blocks in a Gray code ordering scheme which maximizes the data reuse for consecutive block matrix product calculations. Using high-level synthesis optimization, the programmable logic operates at 93% of the theoretical peak performance and the combined CPU-FPGA design achieves 76% of the available hardware processing speed for the floating-point multiplication of 2K by 2K matrices

Variety Steering Concept for Mass Customization

In this paper we make the distinction between subjective and objective customer needs. The subjective needs are the individually realized and articulated requirements, whereas the objective needs are the real ones perceived by a fictive neutral perspective. We show that variety in mass customization has to be orientated on the objective needs. In order to help mass customizers better evaluate the degree to which they can fulfill the objective needs as well as their internal complexity level we have developed a key metrics system model. We also present a conceptual application showing how to use this model to support decision making related to the introduction or reduction of product variants.Variety Management; Complexity; Production/Operations Management