Research On Hierarchical Joint Optimization Problems For Dynamic Postponement Design In Open Manufacturing

Open manufacturing aims to produce products in an open,collaborative and distributed manner based on open source principles.It promotes collaboration across different firms and supports the sharing and exchange of knowledge and services throughout the value chain.The postponement strategy aims to postpone the differentiation of products to the end of supply chain until the customization-specific demand is received.Open manufacturing environment enables more postponement activities to be selected and matched in the product design stage.In practice,successful implementation of postponement strategy in open manufacturing must incorporate its concept as early as possible in the product design stage.However,existing studies on postponement have mainly focused on supply chain management,with limited attention to the inherent coupling of product design and postponement fulfillments in an open manufacturing environment,which entails the necessity of joint decision making for product architecture design and postponement fulfillments of open manufacturing activities.This dissertation emphasizes such a joint decision-making process and formulates the Dynamic Postponement Design(DPD)problems that consider an undefined product architecture that interacts with the postponement fulfillments in an open manufacturing environment.It will inevitably involve multi-agent decision-making and optimization problems in DPD process,which often have a leader-follower structure.Thus,this dissertation formulates the following four Hierarchical Joint Optimization(HJO)problems for DPD in open manufacturing:(1)We firstly research the HJO problem of product family design and postponement fulfillment,and the influences of related suppliers' decision-makings on the optimization problem are considered at the same time.Correspondingly,the HJO problem of product family design and supply chain postponement decision is proposed.A hierarchical interactive decision-making framework between product family design and supply chain postponement decision is constructed.An HJO model with a single manufacturer as the leader and multiple suppliers and contractors as the followers is proposed.Analytical solutions are developed incorporating a genetic algorithm for the proposed HJO model.A case study of electric vehicle postponement is performed to illustrate the effectiveness of the proposed methodology.(2)As the most appropriate postponement type and postponement scheme(contractor)for each postponed product module may be different,the HJO problem of product family design and the selections of postponement type and scheme is proposed.To tackle the HJO problem based the DPD mode,an HJO model based on Stackelberg game theory is developed.The HJO model deploys a bilevel mixed 0-1 nonlinear programming decision structure to reveal the inherent coupling of product design and the selections of postponement type and scheme.To solve the HJO model,a nested genetic algorithm is developed.A case study of smart refrigerator product family design and postponement is reported to demonstrate the feasibility and potential of the proposed HJO approach,and two experiments are designed to compare the obtained results with those results derived from the traditional all-in-one and two-stage methods.(3)Based on the subcontracting decisions or associated supporting behavior of the postponement contractors,we formulate the three-level HJO problem of postponement contracting with subcontracting for product family architecting.A three-level dynamic non-cooperative game framework is constructed with a single manufacturer as the leader,multiple postponement contractors as the followers,and multiple subcontractors as the sub-followers.The interaction among these different stakeholders is modeled as a non-linear,mixed-integer,three-level game-theoretic model based on the Stackelberg game theory.Analytical solutions are developed incorporating a nested genetic algorithm.A practical case study of postponement contracting decisions in an electric vehicle company is reported to verify the feasibility and potential of the proposed HJO approach.(4)Considering that the different postponement fulfillment modes and production technologies have different impacts on the environment,we propose the HJO problem of green product family design and low-carbon postponement fulfillment.A dynamic interactive decision framework with green product family design as the upper level optimization and low-carbon postponement fulfillment as the lower level optimization is constructed.A mixed-integer nonlinear HJO model is developed to characterize the leader-follower decision making process.A nested genetic algorithm is developed and implemented to solve the HJO model.A case study of electric vehicles demonstrates the feasibility and potential of the proposed optimization problem by HJO approach.