2015Research Journal of Applied Sciences Engineering and TechnologyOpen access

Reducing Lead Times in a Two-process Cell Using Lean and Simulation

Charles R. Standridge, Michael J. Maas

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Abstract

An existing power system production process includes two operations and produces twelve different part types. The first operation fills WIP carts used by the second operation. A combined lean and discrete event simulation study supported by the analysis of order history information stored in a corporate information system is presented. The goal was to identify operations alternatives that could be used to reduce customer lead time from the current 3 to 3 days to 1 to 3 days. The application of lean methods included the examination of the order history data that showed that 80% of parts ship to a single primary customer and 20% to many secondary customers. The lean part of the study further concluded that the number of WIP carts should equal the number of different products, that each WIP cart should be associated with one and only one product and that each WIP cart should be should refilled daily after orders are processed. Using a discrete event simulation model, four order processing sequencing alternatives for improving on-time delivery were evaluated. The percent of orders delivered in 1 day was maximized, with the lowest variance, by sorting all orders for the primary customer first from smallest in size to largest. The orders for the same product from the remaining customers are processed immediately after the order for the same product from the primary customer. The value of the synergistic effect of combining lean tools with simulation supported by order data extracted from the corporate information system is demonstrated.

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An existing power system production process includes two operations and produces twelve different part types. The first operation fills WIP carts used by the second operation. A combined lean and discrete event simulation study supported by the analysis of order history information stored in a corporate information system is presented. The goal was to identify operations alternatives that could be used to reduce customer lead time from the current 3 to 3 days to 1 to 3 days. The application of lean methods included the examination of the order history data that showed that 80% of parts ship to a single primary customer and 20% to many secondary customers. The lean part of the study further concluded that the number of WIP carts should equal the number of different products, that each WIP cart should be associated with one and only one product and that each WIP cart should be should refilled daily after orders are processed. Using a discrete event simulation model, four order processing sequencing alternatives for improving on-time delivery were evaluated. The percent of orders delivered in 1 day was maximized, with the lowest variance, by sorting all orders for the primary customer first from smallest in size to largest. The orders for the same product from the remaining customers are processed immediately after the order for the same product from the primary customer. The value of the synergistic effect of combining lean tools with simulation supported by order data extracted from the corporate information system is demonstrated.

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Available abstract

An existing power system production process includes two operations and produces twelve different part types. The first operation fills WIP carts used by the second operation. A combined lean and discrete event simulation study supported by the analysis of order history information stored in a corporate information system is presented. The goal was to identify operations alternatives that could be used to reduce customer lead time from the current 3 to 3 days to 1 to 3 days. The application of lean methods included the examination of the order history data that showed that 80% of parts ship to a single primary customer and 20% to many secondary customers. The lean part of the study further concluded that the number of WIP carts should equal the number of different products, that each WIP cart should be associated with one and only one product and that each WIP cart should be should refilled daily after orders are processed. Using a discrete event simulation model, four order processing sequencing alternatives for improving on-time delivery were evaluated. The percent of orders delivered in 1 day was maximized, with the lowest variance, by sorting all orders for the primary customer first from smallest in size to largest. The orders for the same product from the remaining customers are processed immediately after the order for the same product from the primary customer. The value of the synergistic effect of combining lean tools with simulation supported by order data extracted from the corporate information system is demonstrated.

Key concepts: Discrete event simulation, Sorting, Lead time, Lean manufacturing, Computer science, Cart, Product (mathematics), Process (computing)

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