A vendor-buyer coordinated system featuring an unreliable machine, scrap, outsourcing, and multiple shipments

Abstract

Operating in today's highly competitive global markets, transnational enterprises always seek to optimize internal vendor-buyer coordinated systems to ensure timeliness and quality deliveries, given the reality of unreliable machines and limited capacity. To facilitate accurate decision making to help organizations gain competitive advantages in such situations, this study explores an intra-supply-chain problem featuring a partial outsourcing batch fabrication plan, random scrap, Poisson-distributed breakdown rate, and multiple shipments of end-product. First, we build a model to characterize the problem clearly. Then, we carry out formulations, analyses, and derivations of the model to attain the problem's cost function. We then use differential calculus and propose a specific algorithm to confirm the convexity of the obtained cost function and derive the optimal runtime. Finally, we offer a numerical illustration to demonstrate the result's applicability for other business circumstances. Additional elements of the problem are then discussed, including the individual and combined influence of variations in scrap, outsourcing, breakdown, and shipping frequency. The features of an optimal operating policy and cost relevant parameters are now revealed to assist management with strategic planning and decision making in real-world intra-supply-chain environments.

An operating cost minimization model for buyer-vendor coordination batch system with breakdowns, scrap, overtime, and an external source

“…19. Due to dual utilization-reduction policies (i.e., both outsourcing and overtime options), our utilization reduces to 0.1697 or 33.24% lower than that in a similar study with only outsourcing strategy (Chiu et al, 2020). Moreover, our model's utilization is 42.44% lower than that in a similar model with overtime strategy only.…”

“…Lastly, they employed the utility interval method and provided sensitivity analyses to assess their results and measure their approaches' robustness with a real partner selection case from the Iranian factory. Other studies (Golden and Wiens-Tuers, 2008;Assid et al, 2015;Chiu et al, 2020;Chiu et al, 2021;Cornelius et al, 2021;Chiu et al, 2022;Porto et al, 2022;Chiu et al, 2023;Shekar and Nataraj 2023) discovered the effect of different subcontracting and overtime/output-increasing strategies on reducing batch runtime of modern manufacturing firms' operations and management.…”

Integrating Supply Chain Partners through Implementing Industry 4.0 Technologies to Enhance Competitiveness

“…Open and transparent information exchange facilitates faster decision-making, enables proactive adjustments to changing market conditions, and enhances overall supply chain agility [64,65]. The hybrid decision-making framework in [66] combines mathematical modeling, optimization techniques, and simulation methods to address the challenges inherent in managing such systems effectively. The buyer's involvement in the early design and development phase would improve the producer's performance.…”

Optimizing a multiproduct manufacturing system with delayed differentiation, outsourcing, expedited rate, and rework strategies

“…The researchers first discussed/ evaluated KPIs of a real case of outsourcing information technology services of a telecommunication vendor and then extended to two different settings to demonstrate their evaluation procedures at both client and vendor sides. Recent works [20][21][22][23] also explored the impact of different aspects of adjusted fabrication rate and subcontracting on planning, operations, and management of diverse manufacturing and supply-chain systems. Since few past works have developed a precise model to derive the optimal replenishing policy and explicitly disclose collective/individual impact of postponement, rework, and dual uptime-reduced strategies on the problem's operating cycle policy and crucial performance indices, we aim to serve this purpose and help manufacturers have better control over their operations and facilitate their effective/efficient decision-making.…”