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Optimisation of product family design with consideration of supply risk and discount

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Xinggang Luo at Northeastern University
Xinggang Luo
Wei Li at University of Kentucky
Wei Li
C.K. Kwong at The Hong Kong Polytechnic University
C.K. Kwong
Yan Cao
Yan Cao
Yan Cao
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Abstract and Figures

Optimisation of product family design has been emphasised and studied for many years. However, previous studies only took overall cost or profit as an optimisation objective, but ignored the supply risk of a product family. Moreover, the discount associated with the bidding price, which is common in practice, was not considered in the modelling. In this paper, we propose a new multi-objective optimisation approach integrating supplier selection into product family design. In our optimisation model, not only the profit but also the supply risk of a product family is formulated as optimisation objectives. Consequently, we can evaluate and optimise a product family from many perspectives. In addition, as a bidding price discount may affect product family’s configuration and supplier selection, we include linear piecewise discount of bidding prices from suppliers in our optimisation model. The NSGA-II algorithm is developed to achieve Pareto non-dominated solutions of the multi-objective optimisation model. Sensitivity analysis on the model parameters is performed, and several managerial insights for enterprises are achieved in the case study of a printing calculator product.
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ORIGINAL PAPER
Optimisation of product family design with consideration
of supply risk and discount
Xinggang Luo
1
•Wei Li
2
•C. K. Kwong
3
•Yan Cao
1
Received: 1 January 2015 / Revised: 12 June 2015 / Accepted: 22 September 2015 / Published online: 20 October 2015
Springer-Verlag London 2015
Abstract Optimisation of product family design has been
emphasised and studied for many years. However, previous
studies only took overall cost or profit as an optimisation
objective, but ignored the supply risk of a product family.
Moreover, the discount associated with the bidding price,
which is common in practice, was not considered in the
modelling. In this paper, we propose a new multi-objective
optimisation approach integrating supplier selection into
product family design. In our optimisation model, not only
the profit but also the supply risk of a product family is
formulated as optimisation objectives. Consequently, we
can evaluate and optimise a product family from many
perspectives. In addition, as a bidding price discount may
affect product family’s configuration and supplier selec-
tion, we include linear piecewise discount of bidding prices
from suppliers in our optimisation model. The NSGA-II
algorithm is developed to achieve Pareto non-dominated
solutions of the multi-objective optimisation model. Sen-
sitivity analysis on the model parameters is performed, and
several managerial insights for enterprises are achieved in
the case study of a printing calculator product.
Keywords Multi-objective Product family Supplier
selection NSGA-II
1 Introduction
Currently, mass customisation, which aims at providing
diversified products and services for individual customers
with mass production efficiency, has become the main-
stream production mode (Pine 1993). It has been reported
that mass customisation was successfully applied into
many industrial fields, such as food, electronics, home-
building and large engineering products (Silveira et al.
2001). Recent development and research directions on
mass customisation can be found in the survey paper by
Fogliattoa et al. (2012). As one of the core enabling tech-
nologies of mass customisation, the platform-based product
family refers to a group of products derived from a product
platform (a set of common interfaces, modules or compo-
nents) but with different performances, quality and char-
acteristics. The goal of product family design is to
determine the optimal configurations of product variants in
a product family with the objective of minimising pro-
duction cost or maximising expected profit (Simpson et al.
2006). Recognising the benefits of product family, many
scholars have intensively studied the product family design
problem. Classification and analysis of the related publi-
cations can be found in recent survey papers (Fujita 2002;
Jiao et al. 2007).
On the other hand, to effectively concentrate on the core
competencies and to dominate the market shares, increas-
ing numbers of enterprises choose to outsource the com-
ponents, parts and raw materials of products to external
suppliers. This is further emphasised by the fact that in
many industries, outsourcing costs account for more than
&Xinggang Luo
xgluo@mail.neu.edu.cn
1
Department of Systems Engineering, School of Information,
Northeastern University, Shenyang, Peoples’ Republic of
China
2
Department of Mechanical Engineering, University of
Kentucky, Lexington, KY, USA
3
Department of Industrial and Systems Engineering, The
Hong Kong Polytechnic University, Hung Hom, Kowloon,
Hong Kong, Peoples’ Republic of China
123
Res Eng Design (2016) 27:37–54
DOI 10.1007/s00163-015-0204-1
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... Liu et al. [23] proposed a game-theoretic bilevel optimization approach, which revealed distributed collaborative decision-making inherent in the co-evolution of configuration design and supplier selection for a product family. Luo et al. [24] introduced supply risk into product configuration and proposed an optimization model that maximized the total profit and minimized the supply risk of the whole product family. The decision maker could interactively determine the best solution based on the non-dominant solution set obtained from the model. ...
... In order to improve market competitiveness, enterprises need to reduce the cost of the product family. Variable costs and the fixed cost model were used to calculate the product cost [24,36,37]. The product cost C p i of the ith product variant consisted of the inner-company production cost C in i and outsourcing cost C out i . ...
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