Why Do Companies Need Operational Flexibility to Reduce Waste at Source?

We analyze the environmental benefits of operational flexibility that emerge in the form of less product waste during the sourcing process by reducing overproduction. We consider three different options for operational flexibility: (1) lead-time reduction, (2) quantity-flexibility contracts, and (3) multiple sourcing. We use a multiplicative demand process to model the evolutionary dynamics of demand uncertainty. We then quantify the impact of key modeling parameters for each operational-flexibility strategy on the waste ratio, which is measured as the ratio of excess inventory when a certain operational-flexibility strategy is employed to the amount when an offshore supplier is utilized without any operational flexibility. We find that the lead-time reduction strategy has the maximum capability to reduce waste in the sourcing process of buyers, followed by the quantity-flexibility and multiple-sourcing strategies, respectively. Thus, our results indicate that operational-flexibility strategies that rely on the localization of production are key to reducing waste and improving environmental sustainability at source.

Effect of Lean Practices on Lead Time Reduction

This article presents a study on the effect of Lean practices on lead time reduction. In this study, we have proposed the consideration of human, technical and environmental factors in the study of the impact of production scheduling and SMED on manufacturing lead time. Based on the fact that scheduling and SMED go well beyond a calculation function. From our point of view, it is preferable to broaden the field of study of this impact by going beyond the fields of mathematics, operational research and artificial intelligence. In this study, we propose to start from the idea that there are other factors that can influence the expected results, namely human, technical and environmental factors. To achieve this, we went through a literature review and then tried to validate our hypotheses through a quantitative study.

Application of value stream mapping to enhance productivity by reducing manufacturing lead time in a manufacturing company: A case study

Lead time is a time gap between initiation and completion of the processes or product. The lead time directly affects productivity. Short lead time results in higher output thus add more value in a given period. Value stream map is an effective tool to describe the overall process from order to delivery. In this study, there is lead time reduction by generation current state and future state for a process using various techniques. Thus, the main aim of this work to enhance production by reduction of lead time. Finally, gain in production, reduction in lead time, and reduction in inventory between the stations are also reported.

Shipment sizing for autonomous trucks of road freight

PurposeUnprecedented endeavors have been made to take autonomous trucks to the open road. This study aims to provide relevant information on autonomous truck technology and to help logistics managers gain insight into assessing optimal shipment sizes for autonomous trucks.Design/methodology/approachEmpirical data of estimated autonomous truck costs are collected to help revise classic, conceptual models of assessing optimal shipment sizes. Numerical experiments are conducted to illustrate the optimal shipment size when varying the autonomous truck technology cost and transportation lead time reduction.FindingsAutonomous truck technology can cost as much as 70% of the price of a truck. Logistics managers using classic models that disregard the additional cost could underestimate the optimal shipment size for autonomous trucks. This study also predicts the possibility of inventory centralization in the supply chain network.Research limitations/implicationsThe findings are based on information collected from trade articles and academic journals in the domain of logistics management. Other technical or engineering discussions on autonomous trucks are not included in the literature review.Practical implicationsLogistics managers must consider the latest cost information when deciding on shipment sizes of road freight for autonomous trucks. When the economies of scale in autonomous technology prevail, the classic economic order quantity solution might again suffice as a good approximation for optimal shipment size.Originality/valueThis study shows that some models in the literature might no longer be applicable after the introduction of autonomous trucks. We also develop a new cost expression that is a function of the lead time reduction by adopting autonomous trucks.