Coordinated optimisation of platform-driven product line planning by bilevel programming

Product line planning (PLP) aims at an optimal combination of product feature offerings, suggesting itself to be a determinant decision for a company to satisfy diverse customer needs and gain competitive advantages. Fulfilment of planned product lines must make trade-offs between product variety and production costs. To balance the costs of product lines, manufacturers often adopt a product platform configuration (PPC) approach to redesign product and process platforms by adding new modules to the legacy platforms. The PPC is an effective means of providing product variety while controlling the manufacturing costs. The PLP and PPC problems have traditionally been investigated separately in the marketing research and engineering design fields. It is important to coordinate PLP and PPC decisions within a coherent optimisation framework. This paper proposes a bilevel mixed 0–1 nonlinear programming model to formulate coordinated optimisation for platform-driven product line planning. The upper level deals with the PLP problem by maximising the profit of an entire product line, whilst the lower level copes with the multiple product platforms optimisation for the optimal PPC in accordance with the upper level decisions of product line structure. To solve this bilevel programming model, a bilevel genetic algorithm is developed to find the optimal solution. A case study of coordinated optimisation between an automobile line and its product platforms is presented to demonstrate the feasibility and effectiveness of the proposed bilevel programming in comparison with a typical ‘all-in-one’ approach and a non-joint optimisation programming.     

A re-entrant line model for software product testing

In today’s competitive environment for software products, quality is an important characteristic. The development of large-scale software products is a complex and expensive process. Testing plays a very important role in ensuring product quality. Improving the software development process leads to improved product quality. We propose a queueing model based on re-entrant lines to depict the process of software modules undergoing testing/debugging, inspections and code reviews, verification and validation, and quality assurance tests before being accepted for use. Using the re-entrant line model for software testing, bounds on test times are obtained by considering the state transitions for a general class of modules and solving a linear programming model. Scheduling of software modules for tests at each process step yields the constraints for the linear program. The methodology presented is applied to the development of a software system and bounds on test times are obtained. These bounds are used to allocate time for the testing phase of the project and to estimate the release times of software.     

An integrated framework for product line design for modular products: product attribute and functionality-driven perspective

The purpose of this research is to facilitate original equipment manufacturers operating in a single market segment to frame their product line design strategy that pertains to offering right product attributes with right attribute level in the right product profile within a market segment. Through this research, we attempt to establish a link between functional level design of product attributes with commercial objectives of the enterprise. Initially, by deriving the functional importance of product attribute levels of individual product attributes within a product profile, demand and functional importance data are generated. Utilising the function-based cost estimating framework and multi-linear regression methodology, we determine the cost and product development time coefficients for respective product attributes. Finally, a mixed integer quadratic programming-based mathematical formulation is developed that includes maximisation of product premium and minimisation of various costs as major objectives under the assumption that manufacturer seeks to offer optimal number of product profiles within the market segment. Employing the commercial solver LINGO, the integrated framework is solved. The entire framework is illustrated using the operator cabin of heavy construction machinery.     

The optimisation of maintenance service levels to support the product service system

The dematerialising concept has formed a new management model: the product service system (PSS). PSS means that enterprises have changed the management concept of ‘product foremost and service second’ to ‘service-based product’ in design products, and the products are the tools produced and innovated for service. Therefore, the physical logistical service replaces the virtual service. However, during the transformation, the product service system also needs to emphasise cost, customers’ satisfaction and environmental protection. This study analysed different types of integrated maintenance service and used multi-attribute utility analysis to discuss the overall utility of maintenance service. The operation cost, CO ₂ emission and service satisfaction indicators of different maintenance service models were used as decision variables to determine the optimal maintenance system. Finally, a case study is described to demonstrate this research.     

Cost strategy for product planning under competition

This study proposes a manufacturing system for the production of a new product, which is achieved by optimum collaboration between members of the supply chain. From the perspective of an incumbent firm, the behaviours of randomly occurring competitors could significantly affect order quantities, and the resultant profitability could diminish competitiveness in the product market. An effective method is therefore required to quantitatively evaluate the influence of competitive companies on the incumbent’s profitability. The objective of this study is to minimise the incumbent’s cost for a new product under competition through an economical cost distribution. Considering the whole life of a product in the market, the Bayesian approach is used to analyse the behaviours of competitors, the work efficiency of employees, in addition to the related costs of the incumbent firm. The adequate cost strategy for manufacturing a new product under competition can be then available.     

Product line optimisation based on semiparametric choice model

Consumer choice behaviour is important in the product line optimisation problem. The extant literature on product line optimisation is mostly based on traditional consumer choice models, such as the multinomial logit and multinomial probit models. These models either assume that the utility errors are independent from irrelevant alternatives (IIA) or are limited by complex calculation processes or pre-given, specific distributions of measuring errors. The marginal moment model (MMM), which is classified as a semiparametric choice model, does not require specific distributions of errors; thus, it can overcome the IIA shortcoming. This study focuses on the concavity of the profit functions of a product line optimisation model based on MMM. We prove that the profit function based on MMM is concave in market share under a monopoly or oligopoly. Numerical experiments show that the choice probabilities obtained from the MMM, multinomial logit, and multinomial probit models are similar although they are obtained under different assumptions. Experimental results under monopolistic, Cournot, and Bertrand competition based on MMM are compared. Some interesting managerial insights are summarised based on the sensitivity analysis of the various model parameters.     

A data-driven approach for the optimisation of product specifications

In order to develop the profit-maximising, market share-maximising or cost-minimising bundle of product engineering specifications with proper performance levels, an optimisation model driven by operating data is proposed. The operating data are input as the sources to conduct the optimisation and a data-based customer satisfaction function can be formed. Then, a customer choice model developed from the customer satisfaction is constructed to estimate the customer choice probability. The expected market share (EMS) then can be derived from the choice probability. After all, a multi-objective model is constructed to maximise the EMS and minimise the total engineering cost. The candidate Pareto-optimal solutions can be obtained by solving the optimisation model. Then a membership function is defined to select the optimal solution from the Pareto-optimal solutions. A case study for optimising the smartphone’s specifications is conducted to demonstrate the effectiveness of the newly developed approach. Compared with the commonly used Conjoint Analysis (CA) method in determining the most desired levels for product specifications, the proposed data-driven method can avoid the situation where the user’s preferences are irrational, making the proposed method be more practical in measuring customer preferences than the utility-based model.     

A review and evaluation on constructive heuristics to optimise product mix based on the Theory of Constraints

In this paper, we address the problem of defining the product mix in order to maximise a system's throughput. This problem is well known for being NP-Complete and therefore, most contributions to the topic focus on developing heuristics that are able to obtain good solutions for the problem in a short CPU time. In particular, constructive heuristics are available for the problem such as that by Fredendall and Lea, and by Aryanezhad and Komijan. We propose a new constructive heuristic based on the Theory of Constraints and the Knapsack Problem. The computational results indicate that the proposed heuristic yields better results than the existing heuristic.     

产品包装设计综合评价AMC模型探究

在论述属性数学综合评价模型的基础上,建立了一种多级多因素综合评价方法,并将其应用于产品包装设计综合评价.应用表明,属性数学综合评价模型方便、有效,克服了模糊综合评判中分级不清、结果不合理的问题.     

An intelligent physarum solver for supply chain network design under profit maximization and oligopolistic competition

We propose an efficient bio-inspired algorithm for design of optimal supply chain networks in a competitive oligopoly markets. The firms compete in manufacture, storage and distribution of a product to several markets. Each firm aims at maximisation of its own profit by optimising the design capacity and product flow in the supply chain. We model the supply chain network as a multi-layer graph of manufacturing nodes, distribution nodes and storage centres. To optimise the network, we adopt the mechanisms of a foraging behaviour of slime mould Physarum polycephalym. First, we extend the original Physarum model to deal with networks with multiple sources and sinks. Second, we develop a novel method to solve the user equilibrium (UE) problem by exploiting the adaptivity of the Physarum model: we update the link costs according to the product flow. Third, we refer to an equivalent transformation between system optimum problem and UE problem to determine the optimal product flows and design capacities of a supply chain. At last, we present an approach to update the amount of product supplied by each firm. By comparing our solutions with that in Nagurney (2010b) on several numerical examples, we demonstrate the efficiency and practicality of the proposed method.     

A model for planning the product portfolio and launch timings under resource constraints

Product design is increasingly becoming a critical function in many organisations having significant impact on their performance. It aims at the selection of a near-optimal mix of products and attribute-levels to offer in the target market. The standard product portfolio planning approach has focused on selecting optimum product profiles based on part-worth utility data. However, given that product development happens in multiple stages, combining the product definition decisions with the product development feasibility will provide organisations with a more inclusive and global solution. This paper considers a resource-constrained environment with a multi-stage product development cycle and presents an approach for helping an organisation to select the definitions of products for its product portfolio and the feasible launch timings. The proposed framework will aid product managers and researchers to identify and evaluate alternative product definitions using a Mixed Integer Linear Programming model in order to determine the alternatives which best balance product features and product development.     

A hybrid optimisation approach to configure a supply chain for new product diffusion: a case study of multiple-sourcing strategy

Configuring a supply chain for a new product is a challenging task due to the lack of historical demand data and the dynamic/uncertain nature of the new product diffusion process. An integrated supply chain configuration (SCC) and new product diffusion (NPD) model is developed to explicitly account for the impact of demand dynamics during a new product's diffusion on an optimal supply chain configuration. Our hybrid NPD-SCC model allows a manufacturer to source from multiple suppliers, vendors or modes for its supply chain entities. Such a multiple-sourcing approach not only helps the manufacturer to diversify its pool of suppliers and maintain bargaining power, but also builds redundancy into the supply chain to hedge against potential demand surge and supply disruption during the new product life cycle. Through a case study and a comprehensive computational study, we find that although the single-sourcing solution is able to achieve lower unit-manufacturing cost (UMC), the multiple-sourcing approach is superior to single-sourcing on the overall supply chain performance in the environment with random supply disruptions. By building-in redundancy as multiple suppliers and modes, the resultant supply chain has less chance of being disrupted and achieves higher overall profit on average. We also draw several other managerial insights closing the gap between some supply chain operations and marketing strategies.     

A STEP-compliant product data model for injection moulding products

In the current rapidly changing manufacturing environment, most manufacturing companies have realised that the ability to quickly develop a customised product at competitive prices is very crucial for them to survive in the keen competitive global market. Product modelling has been recognised as one of the key factors in determining the success of various product development strategies and for industrial competitiveness now and in the future. Standard for Exchange of Product model data (STEP) is an international standard designed to provide a complete, unambiguous, computer-readable definition of the physical and functional characteristic of a product through its lifecycle. This paper proposes a STEP-compliant product data model to fully support the complete product information representation and management for injection moulding product development. The data model is developed based on the structure of an injection moulding company. The entire data model consists of six data models which are defined to express information from various departments of the company. The data model is described in EXPRESS language, which can be integrated with other STEP-based product data models and databases. Consequently, the proposed system can be further extended for helping other injection moulding manufacturers to improve their product development process. An information sharing prototype system is implemented based on the proposed product data model to demonstrate the feasibility of the approach.     

A sustainable product design model

There are major challenges for the designer to now include Sustainable Development aspects into his/her design; particularly related to the social and wider economic impacts. The designer must, more than ever before, take into consideration the views and concerns of all the ‘interested parties’ – stakeholders. There are many topics – issues and concerns to consider and often they can be conflicting. The need is to examine the Sustainable Development risks and benefits associated with any particular design so improvements can be made. Both a ‘concept’ model and a Bournemouth University practical model are described which allows this risk/benefit assessment to be made in a structured manner on a wide range of topics. The assessment can examine the product, the company manufacturing the product and the manufacturing site. The major social, economic and environmental risks and benefits is tabulated or presented graphically for ease of evaluation in order to modify the design and so improve the Sustainable Development aspects.     

A morphing method for shape generation and image prediction in product design

A shape morphing and image prediction method for product design is proposed in this article, in which a feature-based method is first used to construct 3-D CAD models of a product, then new shapes are generated with a shape morphing method and the images of the morphed shapes are analyzed using modified gray theory with Fourier residual correction. With the aid of this model, the designer can quickly obtain a product form and its corresponding image to help him/her to design the required product. Though LCD monitor design is applied, this method can also be used to develop other products.     

A mathematical formulation for interface-based modular product design with geometric and weight constraints

Since customer preferences change rapidly, there is a need for design processes with shorter product development cycles. Modularization plays a key role in achieving mass customization, which is crucial in today's competitive global market environments. Standardized interfaces among modularized parts have facilitated computational product design. To incorporate product size and weight constraints during computational design procedures, a mixed integer programming formulation is presented in this article. Product size and weight are two of the most important design parameters, as evidenced by recent smart-phone products. This article focuses on the integration of geometric, weight and interface constraints into the proposed mathematical formulation. The formulation generates the optimal selection of components for a target product, which satisfies geometric, weight and interface constraints. The formulation is verified through a case study and experiments are performed to demonstrate the performance of the formulation.     

A framework for affective customer needs in product design

A systematic framework is proposed to conceptualize customer needs in product design. Customer needs were derived for current and future electronic devices in automobiles. Subjects rated their preferences for 15 product attributes on 10-point semantic differential scales. Using factor analysis, three generic factors were extracted, namely holistic attributes, styling and functional design. Depending upon the familiarity of the device, there were clear differences among potential customers. Unknown devices such as a navigation map were assessed first hand by using holistic attributes. Familiar designs such as car radio and cell phone were assessed using styling and functionality attributes. Customer reactions and preferences may be caused by product design parameters that operate either through their perceptual attributes or from the experience they acquire in using the artifacts or interfaces. There are both functional and affective needs. Functional (or cognitive) customer needs can be derived top-down, using product design features. Affective customer needs are difficult to derive top-down—typically they are evaluated by looking at several design propositions.