生產排程與能耗之整合管理

中文摘要近年來節能的議題受到重視，各領域皆著手探討並發展各式節能方法之可行性，但大多數研究只針對總用電量的優化，並未針對個別工具機之用電內容做進一步分析，故不易針對工具機的差異提出有效的節能決策；此外，雖然已有許多研究提出能源相關的衡量指標，但在工廠層級或針對單一製程卻時常面臨不易於實行的困境，因而產生了學術研究與產業界的落差。本研究針對工具機的差異來分析用電內容，建立生產活動在不同機台上生產的能耗機率模型，可更有效地描述能耗存在不確定性的特性。此外，本研究開發一能耗警示系統，包含「尖峰能耗警示」與「能源效率警示」功能，可快速檢驗生產計劃中能耗期望值較高的排程、找出用電效率較差的工作-機台派工組合，透過視覺化的介面可提供決策者作為調整排程的參考資訊。另一方面，本研究亦提出一加入能耗考量的排程優化方法，由於非相關平行機台彈性製造排程問題為NP-Hard問題，故本研究將問題分解成兩個子問題，第一階段以線性規劃求解派工解，由於線性規劃為最佳化方法，因此可以確保此階段求得的是能源效率最佳的派工解；第二階段以最小化Makespan與超越機率為目標，透過啟發式演算法決定工作順序。透過兩階段排程優化方法，可以求得能源效率最高、完工時間最短、違反契約容量風險最低的排程最佳解。本研究結合能耗警示系統與排程優化演算法，可達到排程與能耗整合管理的目標。

關鍵字

生產排程；能耗管理；生產能耗機率模型

並列摘要

ABSTRACT The concepts of energy saving have been widely discussed during recent years. Various approaches on energy saving have been investigated in different fields. However, most of the researches only aimed at optimizing total power consumption, but failed to examine the detailed electricity usages on every machine respectively. Hence, it was difficult to come up with an effective strategy for energy saving between machines. In addition, although researches have proposed several energy-related evaluative indices, most of these methods are not generally useful for the situations in factory level or single process. Therefore, a deep gap remained between research study and industry practice. In this research, an approach focused on analyzing detailed electricity usage between different machines was proposed. The probability models, which are constructed based on manufacturing activities and mechanical performance, are more efficient when dealing with the uncertainty of power consumption. In addition, an energy alarming system which trigger during High Energy Consumption Alarming and Energy Efficiency Alarming is proposed in this research. It allows managers to evaluate the schedule more efficiently through an interactive visual interface. Furthermore, in this research, an optimization approach for scheduling with consideration of power consumption was developed. Since unrelated parallel machine scheduling problems within flexible manufacturing system are NP-Hard problems, a two stages optimization approach which separates the original problem into two sub-problem is proposed in order to reduce the computation complexity. Through this two stages optimization approach, the multi-criteria, including minimizing total power consumption, minimizing makespan and minimizing the probability of violating contract capacity, could be satisfied. By integrating energy alarming and optimization approach for scheduling, the goal to coordinate and refine scheduling and power consumption management could be achieved.

並列關鍵字

Multi-objective Scheduling ； Power Consumption Management ； Probability Models for Manufacturing Power Consumption

參考文獻

[1] Al-Hamadi, H. M., & Soliman, S. A. (2004). Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model. Electric Power Systems Research, 68(1), 47-59. doi:10.1016/s0378-7796(03)00150-0

[2] Beezão, A. C., Cordeau, J.-F., Laporte, G., & Yanasse, H. H. (2017). Scheduling identical parallel machines with tooling constraints. European Journal of Operational Research, 257(3), 834-844. doi:10.1016/j.ejor.2016.08.008

[3] Ben Taieb, S., Huser, R., Hyndman, R. J., & Genton, M. G. (2016). Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression. IEEE Transactions on Smart Grid, 7(5), 2448-2455. doi:10.1109/tsg.2016.2527820

[4] Boroojeni, K. G., Amini, M. H., Bahrami, S., Iyengar, S. S., Sarwat, A. I., & Karabasoglu, O. (2017). A novel multi-time-scale modeling for electric power demand forecasting: From short-term to medium-term horizon. Electric Power Systems Research, 142, 58-73. doi:10.1016/j.epsr.2016.08.031

[5] Bougain, S., Gerhard, D., Nigischer, C., & Uĝurlu, S. (2015). Towards Energy Management in Production Planning Software Based on Energy Consumption as a Planning Resource. Procedia CIRP, 26, 139-144. doi:10.1016/j.procir.2014.07.093

國際替代計量

生產排程與能耗之整合管理

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