模具製造規劃與排程之機台自動化選擇

現今生活環境中的多數用品，是藉由塑膠射出模具生產多個相同幾何外觀的產品，隨時代潮流演變，模具須因應產品的汰換需求而研發，而模具製造排程屬於零工式排程問題(Job-shop Scheduling Problem)，各零件製程項目與加工時間皆不同，製程之間具有順序關係，必須依照製程序進行排程規劃，在資源有限的情況下，妥善的規劃排程以達到縮短模具製造時間便是一門重要的課題，而工廠的機台數目則是評估生產能力的重要參數之一，增加機台數目，一方面可分散工作量，得以降低單位機台的作業負荷，增加排程調度的靈活性，但相對會增加工廠的資源成本，本研究依加工類別與性質將機台群組化，並模擬人為排程使用的相關經驗法則，以機台待機時間資料作為製程選擇機台的條件，應用關鍵路徑法之概念，定義延遲資料與辨識影響排程工時的主要作業項目，統整人為最佳化的製程交換步驟，藉此開發人工模擬排程最佳化系統，可取代人為指定機台的操作流程，達到自動化選擇機台與排程最佳化的目標，從案例測試結果發現最優能節省約49%的製造時間，並減少17%的機台使用數量，已達到縮短完工時間的目的，根據規劃結果可切換顯示排程路徑甘特圖，更進一步討論瓶頸加工類別的機台數目對製造排程的影響，評估工廠生產績效對於作業量與延遲完工時間之關係，在產品多樣化的市場下，有效的縮短模具開發時間便可提升市場競爭力。

關鍵字

排程最佳化；關鍵路徑法；機台群組化；排程規劃；零工式排程問題

並列摘要

In nowadays surroundings, most products with the same geometrical appearance are produced by mold technology. In response to demands for different products with the times, mold manufacturing technology needs to be developed. Mold manufacture scheduling is a complex Job-shop Scheduling Problem. Different parts have different manufacturing process and operation times. The manufacturing operations must be scheduled and planned in accordance with the sequential relations. With limited resources, the proper schedule is an important issue so as to reduce mold manufacturing time. The number of machines is one of the important parameters of the plant capacity assessment. Increasing the number of machine can disperse works to reduce the machine loading and raise the flexibility of scheduling, but will increase costs. In this study, the machines are grouped by process type and properties, and the study simulate artificial schedule using relevant rule of thumb. The schedule is decided by the standby time of machines. Applying the concept of critical path method defines the data of delayed item, and identifies major operations which affect the program makespan. This research integrates operation exchange process with human optimization in order to develop simulation of artificial scheduling optimization which can replace operational processes about designating machines, and achieve automatic machine selection and schedule optimization. The test results found that manufacturing time can be saved of about 49% and decrease the number of machines by 17% from the case files, and has achieved the purpose of shorter makespan. According to the planning results, users can know the Gantt Chart of scheduling path, and discuss how the delayed machines affect the manufacturing schedule and to evaluate the relationship between the amount of work and delayed time for the industry performance . In the continuously upgrading market, effectively shorten the manufacturing time can enhance competitiveness.

並列關鍵字

Scheduling Optimization ； Job-shop Scheduling Problem ； Planning and Scheduling ； Machine Group ； Critical Path Method

參考文獻

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[3]. Webster, S., Jog, D. & Gupta, A. (1998). A Genetic Algorithm for Scheduling Job Families on a Single Machine with Arbitrary Earliness/Tardiness Penalties and an Unrestricted Common Due Date. International Journal of Production Research, 36(9), 2543-2551.

[4]. Adamopoulos, G. I. & Pappis, C. S. (1996). Scheduling Jobs with Different, Job-dependent Earliness and Tardiness Penalties Using the SLK Method. European Journal of Operational Research, 88(2), 336-344.

[5]. Cheng, R., Gen, M. & Tsujimura, Y. (1999). A Tutorial Survey of Job-Shop Scheduling Problems Using Genetic Algorithms, Part Ⅱ: Hybrid Genetic Search Strategies. Computer and Industrial Engineering, 36(2), 343-364.

[7]. Adams, J., Balas, E. & Zawack, D. (1988). The Shifting Bottleneck Procedure for Job Shop Scheduling. Management Science, 34(3), 391-401.

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模具製造規劃與排程之機台自動化選擇

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