Integrated optimisation for production capacity, raw material ordering and production planning under time and quantity u
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Integrated optimisation for production capacity, raw material ordering and production planning under time and quantity uncertainties based on two case studies Wei Xu1 · Dong‑Ping Song2 Received: 27 November 2019 / Revised: 1 September 2020 / Accepted: 21 September 2020 © The Author(s) 2020
Abstract This paper develops a supply chain (SC) model by integrating raw material ordering and production planning, and production capacity decisions based upon two case studies in manufacturing firms. Multiple types of uncertainties are considered; including: time-related uncertainty (that exists in lead-time and delay) and quantityrelated uncertainty (that exists in information and material flows). The SC model consists of several sub-models, which are first formulated mathematically. Simulation (simulation-based stochastic approximation) and genetic algorithm tools are then developed to evaluate several non-parameterised strategies and optimise two parameterised strategies. Experiments are conducted to contrast these strategies, quantify their relative performance, and illustrate the value of information and the impact of uncertainties. These case studies provide useful insights into understanding to what degree the integrated planning model including production capacity decisions could benefit economically in different scenarios, which types of data should be shared, and how these data could be utilised to achieve a better SC system. This study provides insights for small and middle-sized firm management to make better decisions regarding production capacity issues with respect to external uncertainty and/or disruptions; e.g. trade wars and pandemics. Keywords Multi-stage supply chain · Raw material ordering and production planning · Capacity planning · Uncertainties · Case study · Genetic algorithms
* Dong‑Ping Song [email protected] Wei Xu [email protected] 1
Material System Co., Ltd., Shanghai, China
2
School of Management, University of Liverpool, Chatham Street, Liverpool L69 7ZH, UK
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Vol.:(0123456789)
W. Xu, D.-P. Song
1 Introduction In the Supply Chain (SC) context, a wide range of decisions could influence Supply Chain Performance (SCP); e.g. management of material inputs and outputs, production and transport planning, coordination among SC facilities, demand forecasting, and information management. To establish a fully collaborative decision-making mechanism that benefits the whole SC, as well as each member is a complex and challenging process. Managing Raw Materials (RMs) ordering and production planning ensures companies having required materials to build or produce a product with lower cost (cost is accrued at the point of acquisition and is listed as a current asset on a company’s balance sheet). Production capacity limits the income when the product is in high demand, but increases the potential cost during times of low demand. Integrated decisions are especially complicated and difficult when the SC faces disruption (e.g. trade war or natural disaster). Thus, it is important
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