Concurrent product configuration and process planning, towards an approach combining interactivity and optimality

Abstract

In mass customisation, defining concurrently the configured product and the planning of the associated production process is a key issue in the customer/supplier relationship. Nevertheless, few studies propose supporting the decision-maker during the resolution of this significant problem. After studying the decision-maker's needs and problem characterisation (modelling and scale aspects), we propose in this paper a two-step approach with the aid of some tools. The first step allows the customer or internal requirements to be captured interactively with a constraint-based approach. However, this step does not lead to one single solution, e.g. there are many uninstantiated remaining decision variables. In this paper, we suggest adding an original optimisation step to complete this task. Thus, the contribution of the study is twofold: first, methodologically to define a new two-step approach that meets industrial needs; and second, to provide adapted tools especially for the optimisation step. The optimisation step, using a multi-criteria constrained evolutionary algorithm, allows the user to select their own cost/cycle time compromise among a set of Pareto optimised solutions. A conventional evolutionary algorithm is adapted and modified, with the inclusion of filtering processing, in order to avoid generating invalid solutions. Experimentations are described, and a comparison is made with a branch-and-bound approach that outlines the interest in the propositions.

A multi-population co-evolutionary genetic programming approach for optimal mass customisation production

“…In most of the presently developed concurrent design methods for mass customisation production, only design and one of the downstream product development life cycle aspects such as manufacturing process are considered Pitiot et al 2013). Quality of the mass customised product can be improved by incorporating considerations in more downstream product development life cycle activities such as manufacturing resource planning and maintenance process planning.…”

“…Zhang, Huang, and Rungtusanatham (2008) developed a mixed integer programming model that integrated both platform product design and material purchase decisions based on cost drivers that were sensitive to commonality and modularity. Pitiot et al (2013) introduced a two-step approach to conduct concurrent product configuration and process planning, where the first step was to capture the customer or internal requirements interactively with a constraint-based approach and the second step was to identify the optimal solution through a multi-criteria constrained evolutional optimisation algorithm.…”

Readiness, feasibility and confidence: how to help bidders to better develop and assess their offers

“…With the previous problem descriptions, Pitiot, Aldanondo, and Vareilles (2014) and Pitiot et al (2012) have suggested (i) combining these two problems into a single one and (ii) considering this concurrent problem as a single CSP. Viewing this concurrent configuration problem as a single CSP allows propagation or constraint filtering mechanisms to be used as an aiding tool.…”

Customer/Supplier Relationship: reducing Uncertainties in Commercial Offers thanks to Readiness, Risk and Confidence Considerations

“…Each time a customer's expectation is inputted (mainly in the product and less in the process), constraints propagate this decision and prune variables values for descriptive attributes, component families, resources families, resources quantities, operation duration and then update performance, cycle time and total cost. For a detail presentation with an easy to understand example, we deeply suggest to consult [13]. This kind of problem modeling is the ground basis of configuration problems.…”