In order to make the largest profits for manufacturers in build-to-order (BTO) supply chain environment, order acceptance decision models are presented. Manufacturer with finite production capacity has ability to select lead-time flexibility in BTO supply chain environment. Two order processing method, i.e., split-lot processing and whole-lot processing, are considered. How the different lead-time flexibility and various manufacturing environment influence profits and the choice of order acceptance is analyzed through a numeric example. Numerical analyzes show that whatever the environment is, profits gained from split-lot order processing is always higher than from whole-lot order processing. The conclusion can provide manager with useful guidance during order acceptance selection.
Considering the problem that the process quality state is difficult to analyze and monitor under manufacturing big data, this paper proposed a data cloud model similarity-based quality fluctuation monitoring method in data-driven production process. Firstly, the randomness of state fluctuation is characterized by entropy and hyperentropy features. Then, the cloud pool drive model between quality fluctuation monitoring parameters is built. On this basis, cloud model similarity degree from the perspective of maximum fluctuation border is defined and calculated to realize the process state analysis and monitoring. Finally, the experiment is conducted to verify the adaptability and performance of the cloud model similarity-based quality control approach, and the results indicate that the proposed approach is a feasible and acceptable method to solve the process fluctuation monitoring and quality stability analysis in the production process.
Aiming at the high cost of multicategory orders fulfillment under multiwarehouse collaborative distribution, comprehensively considering the fulfillment costs of different orders fulfillment strategies, an order fulfillment strategy selection model is proposed. The first step of the model uses the linear programming algorithm to solve the cost of suborder merge transportation after the order is split. The second step calculates the cost of the current “greedy algorithm” of the e-commerce platform for order split fulfillment. Then, the cost of each strategy is compared and the lowest cost one is chosen. The calculation example analysis shows that the order fulfillment strategy is closely related to the delivery location of the order and the SKU category. When the delivery location is far away and SKU categories are many in the order, the merged transportation strategy of suborders after the order is split will be significantly better than the cost of separate transportation. The multiwarehouse collaborative distribution fulfillment strategy proposed in this paper can provide a decision basis for the e-commerce platform to choose which fulfillment method.
In order to coordinate time-varying price supply chain with inequity-averse retailers, this paper proposes a cooperative system decision model based on buy-back contract. The model concentratedly takes the market demand, manufacturers’ order response time, retailers’ inequity aversion, and time-varying price into consideration. Through sensitivity analysis of model parameters, the influence of inequity aversion characteristics of retailers on contract parameters is analyzed by a numerical example. The result reveals that the cooperative system based on buy-back contract can coordinate such supply chains. And it shows that when the retailer has disadvantageous inequity aversion, the buy-back contract is beneficial to the manufacturer; when the retailer has advantageous inequity aversion, the buy-back contract is beneficial to the retailer.
A joint contract is proposed to coordinate the time-varying supply chain of risk-averse manufacturers and retailers. The joint contract uses price reduction subsidies and revenue-sharing strategies to enable manufacturers and retailers to share risks and achieve overall coordination of the supply chain. Firstly, a centralized and a decentralized decision-making model of the risk-averse supply chain are established. On this basis, reasons for the supply chain failure to coordinate are analyzed, and a joint contract is designed. Then, the specific form of the joint contract is given. Finally, the coordination effect of the joint contract is quantitatively analyzed through numerical analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.