PurposeThis paper seeks to analyse the internal materials flow in lean manufacturing in an assembly line of the Bosch factory, located in Spain. The objective is to develop a handling system in a small space, capable of solving the problems of accumulated intermediate stocks of parts. An improvement is proposed adopting the milkrun handling system, while verifying the advances by means of lean metrics.Design/methodology/approachBased on this case study, the paper identifies data from value stream mapping and uses lean metrics, such as dock‐to‐dock time and lean rate. The case study develops a timetable and routing analysis for the milkrun to improve materials flow.FindingsThe proposed logistics allows an improvement of lean metrics, without modifying the layout and production planning. The routing flexibility of the milkrun reduced stocks, work‐in‐process and dock‐to‐dock time, while increasing lean rate.Research limitations/implicationsThe findings are limited due to the focused nature of the case study. Although the solution is designed for a particular plant, the methodology is fully exportable.Practical implicationsThe paper shows a real case study illustrative for systems management. This research shows significant benefit associated with the implementation of lean programs.Originality/valueIt details how the application of lean manufacturing tools could necessitate a study of materials handling to improve lean metrics.
Manufacturing flexibility is becoming a fundamental production objective, along with cost, quality, and delivery time. Current production systems face quick changes in market conditions and they need to adapt in this environment. The supply chain and industrial globalization give an important role for assembly systems. Placed at the end of the value chain, assembly systems must face those quick changes successfully to reach the expected performance. The key performance indicators are normally based on cost, quality, and delivery time objectives. Reducing costs and improving quality are almost universal goals. Delivery time is typically determined by customer demand in the supply chain, planning from make-to-stock to make-to-order, and aspiring to reach a just-in-time manufacturing system. In this context, flexibility could be the differential advantage to tackle uncertainty. Closely related to the rest of production objectives and the overall performance of the system, flexibility must be integrated in the system for successful decision-making in operations. This work presents this approach of flexibility. A brief review of flexibility concepts and measurements in the literature precedes an introduction to flexibility, defined based on the function of utility. This function represents the expectations of system performance. This approach allows the formulation of the taxonomy of operational flexibility in agreement with the classical types identified in former works. Next, an integer model is programmed to simulate the basic behavior of task planning in a make-to-order assembly system. This first application illustrates flexibility quantification based on utility evolution. The use of common industrial parameters to quantify operational flexibility will finally facilitate an integrated interpretation of system performance trends.
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