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Mathematical modelling of products allocation to customers for semiconductor supply chain

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dc.contributor.author Mousavia, Behrouz Alizadeh
dc.contributor.author Azzouza, Radhia
dc.contributor.author Heavey, Cathal
dc.date.accessioned 2020-05-21T10:44:04Z
dc.date.available 2020-05-21T10:44:04Z
dc.date.issued 2019
dc.identifier.uri http://hdl.handle.net/10344/8840
dc.description peer-reviewed en_US
dc.description.abstract Where demand outstrips supply, there will result in shortages to end customers. In such a case decisions need to be made of how to allocate supply to customers. Customer satisfaction requires accurate order promising that leads to better cooperation, as well as trustable orders and forecasts from customers. As a result, customer satisfaction through a trustable promising system leads to more accurate planning for production. In this regard, modern Advanced Planning Systems (APS) provides allocation planning to customers’ orders based on “Available To Promise” (ATP). Lack of supply, escalation, and excess demand are propelled by competitive plant capacity, dynamic behaviours of ATP, orders, and demand forecasts in demanding industries like semiconductor manufacturing. When demand exceeds supply, APS needs the support of experts (human intervention) about the time and amount to be allocated to customers. This feature of APS keeps the flexibility of planning to find feasible optimal decisions regarding allocations. In this paper, we propose a mathematical model for the optimization of ATP allocation to customers, where demand exceeds supply, which will be presented as a decision support tool to analyse allocation scenarios. The objective of the proposed mathematical model is maximizing customer service level which is directly related to customer satisfaction while keeping a maximum of stock. The model is being developed from a case study of a European semiconductor supply chain with a sales office in Ireland. en_US
dc.language.iso eng en_US
dc.publisher Elsevier en_US
dc.relation 737459 en_US
dc.relation.ispartofseries Procedia Manufacturing;(29th FAIM2019)
dc.subject Order Managemen en_US
dc.subject Allocation Planning en_US
dc.subject Customer Satisfaction en_US
dc.subject Optimization en_US
dc.title Mathematical modelling of products allocation to customers for semiconductor supply chain en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1016/j.promfg.2020.01.190
dc.contributor.sponsor ERC en_US
dc.contributor.sponsor SFI en_US
dc.relation.projectid 737459 en_US
dc.relation.projectid 16/RC/3918 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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