Applications of Implosion in Manufacturing

Dietrich, Brenda; Connors, Daniel P.; Ervolina, Thomas R.; Lougee-Heimer, Robin; Wittrock, Robert J.; Fasano, J.P.

doi:10.1007/3-540-27354-9_5

Cited by 9 publications

(5 citation statements)

References 12 publications

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“…The ATP process utilizes an analytical technique called implosion to generate an optimized ATP schedule that takes into account supplier commitments and limited manufacturing capacities (e.g., Dietrich et al 2005). Because the implosion technology has no means of dealing with unallocated supply, a separate non-integrated business process is often created to manage inventory excess and overages, e.g.…”

Section: Ervolina Ettl Lee and Petersmentioning

confidence: 99%

“…Chen-Ritzo (2006) studies the availability management process for CTO system with order configuration uncertainty and formulates a two stage stochastic linear program with recourse that is solved using a sample average approximation method. Dietrich et al (2005) describe an Available-To-Sell (ATS) implosion model that finds marketable products that consume the excess while minimizing additional component purchasing costs. Akcay and Xu (2004) develop a two-stage stochastic integer program with recourse to allocate constrained components so as to maximize the fraction of orders assembled within a quoted maximum delay.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simulating Order Fulfillment with Product Substitutions in an Assemble-To-Order Supply Chain

Ervolina¹,

Ettl²,

Lee³

et al. 2006

Proceedings of the 2006 Winter Simulation Conference

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In today's competitive and dynamic business environment, companies need to continually evaluate the effectiveness of their supply chain and look for ways to transform business processes to achieve superior customer service and higher profitability. In this paper we propose a novel availability management process called Available-to-Sell (ATS) that incorporates demand shaping and profitable demand response to drive better operational efficiency through improved synchronization of supply and demand. We develop an order fulfillment simulation model to assess how the proposed availability management system affects supply chain performance, and apply the model in a server computer manufacturing environment. The simulation plays an important role in making strategic business decisions that impact customer service, revenue and profitability.

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Section: Ervolina Ettl Lee and Petersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simulating Order Fulfillment with Product Substitutions in an Assemble-To-Order Supply Chain

Ervolina¹,

Ettl²,

Lee³

et al. 2006

Proceedings of the 2006 Winter Simulation Conference

Self Cite

View full text Add to dashboard Cite

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“…In industries, the capability for constrained planning has been incorporated in some of the advanced supply chain solutions. For example, the IBM Implosion Technology described in Dietrich et al (2005) is capable of solving a variety of complex manufacturing planning problems including those with materials and capacity constraints in a deterministic setting. Particularly, the heuristic-based planning engine based on the implosion technology has the capability of optimizing capacity utilization by allowing sub-assemblies to be built early.…”

Section: Literature Reviewmentioning

confidence: 99%

A Production–Inventory Model for a Push–Pull Manufacturing System with Capacity and Service Level Constraints

Cheng

Ettl²,

Lu³

et al. 2012

Production and Operations Management

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We study a hybrid push–pull production system with a two‐stage manufacturing process, which builds and stocks tested components for just‐in‐time configuration of the final product when a specific customer order is received. The first production stage (fabrication) is a push process where parts are replenished, tested, and assembled into components according to product‐level build plans. The component inventory is kept in stock ready for the final assembly of the end products. The second production stage (fulfillment) is a pull‐based assemble‐to‐order process where the final assembly process is initiated when a customer order is received and no finished goods inventory is kept for end products. One important planning issue is to find the right trade‐off between capacity utilization and inventory cost reduction that strives to meet the quarter‐end peak demand. We present a nonlinear optimization model to minimize the total inventory cost subject to the service level constraints and the production capacity constraints. This results in a convex program with linear constraints. An efficient algorithm using decomposition is developed for solving the nonlinear optimization problem. Numerical results are presented to show the performance improvements achieved by the optimized solutions along with managerial insights provided.

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“…In the manufacturing supply chain, this might be a set of components that are produced by a certain manufacturing step, which itself consumes some set of parts and capacities. RCP is built using the Watson Implosion Technology (WIT) toolkit [5,6], which consists of a resource capacity model, solvers, and an Application Programming Interface (API). This paper describes the kinds of problems that RCP addresses and discusses how some of the unique attributes of the human resource supply chain were incorporated into the RCP models.…”

Section: Introductionmentioning

confidence: 99%

Applying supply chain optimization techniques to workforce planning problems

et al. 2007

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The IBM Research Division has developed the Resource Capacity Planning (RCP) Optimizer to support the Workforce Management Initiative (WMI) of IBM. RCP applies supply chain management techniques to the problem of planning the needs of IBM for skilled labor in order to satisfy service engagements, such as consulting, application development, or customer support. This paper describes two RCP models and presents two approaches to solving each of them. We also describe the motivation for using one approach over another. The models are built using the Watson Implosion Technology toolkit, which consists of a supply chain model, solvers for analysis and optimization, and an Application Programming Interface (API) for developing a solution. The models that we built solve two core resource planning problems, gap/glut analysis and resource action planning. The gap/glut analysis is similar to material requirements planning (MRP), in which shortages (gaps) and excesses (gluts) of resources are determined on the basis of expected demand. The goal of the resource action planning problem is to determine what resource actions to take in order to fill the gaps and reduce the gluts. The gap/glut analysis engine is currently deployed within the IBM service organization to report gaps and gluts in personnel.

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Applications of Implosion in Manufacturing

Cited by 9 publications

References 12 publications

Simulating Order Fulfillment with Product Substitutions in an Assemble-To-Order Supply Chain

Simulating Order Fulfillment with Product Substitutions in an Assemble-To-Order Supply Chain

A Production–Inventory Model for a Push–Pull Manufacturing System with Capacity and Service Level Constraints

Applying supply chain optimization techniques to workforce planning problems

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