Production and Predictive Maintenance Policies for Deteriorated Products under Advance-cash-credit Payments
碩士 === 國立臺灣科技大學 === 工業管理系 === 106 === In the era of industry 4.0, manufacturers tend to integrate predictive maintenance into production systems to maximize lifespan of equipment and avoid costly disruptions. Through the use of IoT sensors and data analysis, predictive maintenance can substantially...
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| Format: | Others |
| Language: | en_US |
| Published: |
2018
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| Online Access: | http://ndltd.ncl.edu.tw/handle/w5926s |
| Summary: | 碩士 === 國立臺灣科技大學 === 工業管理系 === 106 === In the era of industry 4.0, manufacturers tend to integrate predictive maintenance into production systems to maximize lifespan of equipment and avoid costly disruptions. Through the use of IoT sensors and data analysis, predictive maintenance can substantially reduce production downtime by detecting and predicting systems before out of control resulting in a lower defective rate. Additionally, advance-cash-credit (ACC) payment scheme is commonly applied in real world business transaction to enhance cash flow flexibility among supply chain members. This paper develops a supplier-manufacturer chain which a predictive maintenance adopting manufacturer receives an ACC payment from the supplier to display supply chain management situation within the imperfect economic production quantity (EPQ) framework. Then, we model the manufacturer’s inventory system as a profit maximization problem to determine the optimal replenishment cycle time and predictive maintenance effort for deteriorated product. This model also adopts the discounted cash-flow analysis to consider time value of optimal profit which is proved to strictly concave in both replenishment time and preventive maintenance effort. Numerical and sensitivity analysis then are conducted to illustrate the effectiveness of proposed model. Finally, management insights are provided based on the result of model.
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