Cost Minimization for a Multi-Product Fabrication-Distribution Problem with Commonality, Postponement, and Quality Assurance

Abstract

To gain more competitive advantages and attract more customers from the turbulent business environment, manufacturing firms today must offer a wide variety of products to marketplaces. The existence of component commonality in multi-product fabrication planning enables managers to reevaluate different production design alternatives to lower overall production relevant costs. Motivated by assisting managers of manufacturing firms in gaining competitive advantages, maximizing machine utilization, and reducing overall quality and fabrication-distribution costs, this study explores a multi-product fabrication-distribution problem with component commonality, postponement, and quality assurance. A two-stage single-machine production scheme with the reworking of repairable nonconforming items is proposed. The first stage fabricates common intermediate components for all products, and the second stage produces and distributes end products under a common cycle time policy. Mathematical modeling and optimization techniques are utilized to derive the optimal fabrication-distribution policy that minimizes the expected total system costs of the problem. Finally, we provide a numerical example with sensitivity analyses to not only show practical uses of the obtained results, but also demonstrate that the proposed production scheme is beneficial in terms of cost savings and cycle time reduction as compared to that in a single-stage production scheme. The research results enable manufacturers to gain more competitive advantages in the turbulent global business environment.

Note on cost minimization for a multi-product fabrication- distribution problem with commonality, postponement and quality assurance

“…Moreover, in the planning stage of fabrication, when multiproduct sharing a common component, the delayed differentiation strategy is constantly taken into consideration to cut short the cycle time and/or reduce total system cost (Swaminathan, & Tayur, 1998;Abbad, & Zahratahdi, 2008;Bernstein, DeCroix, & Wang, 2011;Chiu, Kuo, Chiu, & Chang, 2019). Motivated by the benefit of applying postponement strategy to the real vendor-buyer systems, Chiu, Kuo, Chiu and Chiu (2016) studied a multiproduct fabrication-shipment problem featuring postponement and product quality reassurances using mathematical modeling and differential calculus to decide the optimal operating decisions. They also demonstrated that various benefits (in terms of reduction of cycle length and system) can be gained from their research results.…”

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A multiproduct fabrication-shipment problem with postponement and quality reassurance was explored (Chiu et al, 2016) to minimize overall relevant system costs, in which the differential calculus was utilized in the optimization procedure to help decide the optimal fabrication-distribution policy. This research note presents a two-phase algebraic approach, in lieu of their derivatives, to find the optimal policy to the problem.

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Optimization of an intra-supply chain system with unreliable production facility

“…With the help of a recursive algorithm they were able to locate the optimal fabrication runtime. Other studies [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39] also addressed diverse aspects of fabrication systems featuring defective products, rework, and stochastic failure of equipment. This paper extends a prior study (Chiu [01]) by incorporating the shipping cost of end products and stock holding cost of sales offi ces into Chiu's model and resolves the optimal replenishment cycle time for such an intra-supple chain system.…”

Solving a Fabrication Lot-Size and Shipping Frequency Problem with an Outsourcing Policy and Random Scrap

“…Transportation cost was explicitly incorporated into their system and its cost minimization solution process to obtain the optimal operating policy. Additional studies related to different aspects of supply-chain systems with multi-shipment policy can also be referred elsewhere [32][33][34][35][36][37][38][39][40]. With the aim of providing managers of intra-supply chain systems with insight information to support their decision makings, this study incorporates a beneficial outsourcing option into a prior work [18], and explores the optimal replenishment lot-size and shipping frequency problem with a partial outsourcing policy and random scrap.…”