{"title":"不确定约束和不确定性预测下包装行业库存单位优化","authors":"Ab Boxley, Marcelo Costa de Sousa, Ashish Singh","doi":"10.1109/SIEDS.2019.8735631","DOIUrl":null,"url":null,"abstract":"In a competitive industry like corrugated packaging, companies are constantly looking for opportunities to increase the efficiency of operations while maintaining high standards of customer service. This paper presents a multi-faceted approach to a large player in this industry, incorporating demand trends for different packaging specifications to optimize raw material and tooling dimensions, and rebalance production costs and wastage at the conversion facility. Given the market dynamics, a value-creating solution needs to be able to capture fluctuations in demand including unexpected orders from key customers requiring individual treatment. We propose a process-driven solution incorporating both a supply chain communications methodology and a simulation-based tool that managers can rely on to guide the selection of tooled SKUs to be maintained in the production line. To provide the user with realistic optionality, both assumptions and sensitivities are employed surrounding parameters such as service level, lead time, and cost variances. The resultant suite combines a series of optimization algorithms that are aligned with inventory management best practices and produce an application that is relevant, applicable, and flexible enough for business managers to make decisions on the fly and reach an optimal solution given the restrictions imposed by the operation.","PeriodicalId":265421,"journal":{"name":"2019 Systems and Information Engineering Design Symposium (SIEDS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimizing Stock Keeping Units (SKUs) in the Packaging Industry Managing for Indefinite Constraints and Forecasting Uncertainty\",\"authors\":\"Ab Boxley, Marcelo Costa de Sousa, Ashish Singh\",\"doi\":\"10.1109/SIEDS.2019.8735631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a competitive industry like corrugated packaging, companies are constantly looking for opportunities to increase the efficiency of operations while maintaining high standards of customer service. This paper presents a multi-faceted approach to a large player in this industry, incorporating demand trends for different packaging specifications to optimize raw material and tooling dimensions, and rebalance production costs and wastage at the conversion facility. Given the market dynamics, a value-creating solution needs to be able to capture fluctuations in demand including unexpected orders from key customers requiring individual treatment. We propose a process-driven solution incorporating both a supply chain communications methodology and a simulation-based tool that managers can rely on to guide the selection of tooled SKUs to be maintained in the production line. To provide the user with realistic optionality, both assumptions and sensitivities are employed surrounding parameters such as service level, lead time, and cost variances. The resultant suite combines a series of optimization algorithms that are aligned with inventory management best practices and produce an application that is relevant, applicable, and flexible enough for business managers to make decisions on the fly and reach an optimal solution given the restrictions imposed by the operation.\",\"PeriodicalId\":265421,\"journal\":{\"name\":\"2019 Systems and Information Engineering Design Symposium (SIEDS)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Systems and Information Engineering Design Symposium (SIEDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIEDS.2019.8735631\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Systems and Information Engineering Design Symposium (SIEDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIEDS.2019.8735631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing Stock Keeping Units (SKUs) in the Packaging Industry Managing for Indefinite Constraints and Forecasting Uncertainty
In a competitive industry like corrugated packaging, companies are constantly looking for opportunities to increase the efficiency of operations while maintaining high standards of customer service. This paper presents a multi-faceted approach to a large player in this industry, incorporating demand trends for different packaging specifications to optimize raw material and tooling dimensions, and rebalance production costs and wastage at the conversion facility. Given the market dynamics, a value-creating solution needs to be able to capture fluctuations in demand including unexpected orders from key customers requiring individual treatment. We propose a process-driven solution incorporating both a supply chain communications methodology and a simulation-based tool that managers can rely on to guide the selection of tooled SKUs to be maintained in the production line. To provide the user with realistic optionality, both assumptions and sensitivities are employed surrounding parameters such as service level, lead time, and cost variances. The resultant suite combines a series of optimization algorithms that are aligned with inventory management best practices and produce an application that is relevant, applicable, and flexible enough for business managers to make decisions on the fly and reach an optimal solution given the restrictions imposed by the operation.