بررسی مقایسه ای کاربردپذیری مدل های فازی برنامه ریزی خطی چندهدفه از طریق تجزیه و تحلیل مقرون به صرفه برای تولید قالب

The mold-manufacturing process consists of prototype design, production, assembly, and testing. As products tend to vary, have short due dates, and life cycles, are highly precise and must be responsiveness to customers, production system planning is complex and the relationship between outsourcing capability and in-house capacity is crucial to mold-manufacturing. Differentiation of core operations vs. non-core operations in internal vs. external environments and time control are essential for mold manufacturing when planning production systems. To analyze the cost-effectiveness of capacity planning and its relationship to suppliers, this work applies a novel fuzzy multi-objective linear programming model. Considered factors are order quantity allocation, due dates, manufacturing quantity, capacity, defect rates, back-log, and the purchasing discount. The applicability of three fuzzy theories is assessed using total costs, punishment costs, and crashing costs. Implementation results demonstrate the potentials for cost-effective capacity planning and outsourcing, and identify the applicability of these fuzzy theories to a specific mold-manufacturing case.

Since the early 1960s, Taiwan's mold products have performed well as industrial exports. Almost all industries require support from the mold industry. However, since high-tech industries require highly precise molds, limited production, diverse models, short product life-cycles, and the need for rapid responses to customers have made decisions for mold production planning more complex than ever before. Low-end products are no longer competitive and high-end products are diversely impacted by changing production systems. Mold-production systems require technological evaluation in the design phase to enhance production efficiency and rapidly respond to customer requirements in the manufacturing phase. In the design or manufacturing phase, mold-manufacturing firms must examine product prototypes, evaluate part designs, and monitor manufacturing progress (Li et al. [1]). Further, order releasers are willing to be involved in the design phase to ensure adequate monitoring of outsourced manufacturing and acquire high-value products in competitive business environments (Cordero et al. [2]). Collaboration between mold firms and outsourcers is therefore important for the mold-manufacturing chain (Ybarra and Turk [3]). As many high-tech enterprises have global supply chains, Taiwanese mold firms must determine how to best develop a new strategy to maintain cost-effective manufacturing and upgrade products simultaneously. To develop a cost-effective production system, firms must adjust their make/buy ratio in outsourcing decisions and enhance manufacturing flexibility. As customers continually request improvements in product quality, factors in cost-effective decisions are extended to technological evaluations of outsourced firms. To retain customers and respond rapidly to their needs, mold firms must improve their productivity (Ni et al. [4]). Specifically, the make/buy ratios associated with quality improvement, due-date responsiveness, cost control, and supply flexibility must be considered. Thus, a cost-effective model is needed to analyze factor interactions. Conversely, a lack of technological expertise may cause production management problems related to lateness costs, rework costs, crashing, inspection, and product lifecycle (Lan [5]; Wang et al. [6]). The mold-manufacturing process has three basic steps: initial product design; coarse electrical discharge machining (EDM); and, product forming. To establish competitive advantage, collaborative operations of vertical or horizontal alliances in outsourcing are crucial (Alemany et al. [7]). However, significant improvements in process efficiency may be achieved by process parameter optimization that identifies and determines regions of critical process-control factors, leading to desired responses with acceptable variations and ensuring reduced manufacturing costs (Montgomery [8]). Outsourcing strategies are often utilized to satisfy demand within a limited capacity; however, firms should consider the technological variation environment. Capacity expansion and partial outsourcing are two strategies commonly used to meet market demands (Wang et al. [9]). Mold-production processes involve many planning steps with decision-making in different phases. Mold-manufacturing technology directly affects product quality, and manufacturers must continually optimize their development strategy based on cost-effectiveness (Law [10]). Additionally, mold manufacturing uses the make-to-order (MTO) production mode. As each product is unique, each technology must be examined, such that customer requirements can be satisfied (Raturi et al. [11]). A strategic alliance is critical to achieving competitive advantage (Ybarra and Turk [3]). To respond quickly to customer requirements, outsourced firms should be involved in designing products and share their knowledge and expertise (Andersen and Drejer [12]). Given a specific quality requirement, purchasing discount, and lead time with cost determinants, mold-production planners must evaluate production options under contractual requirements, manufacturing capability, and the capabilities of outsourced firms. To evaluate the effects of outsourcing and capacity-expansion decisions on cost-effectiveness while considering multiple parts and suppliers, this work applies a novel fuzzy multi-objective model. To evaluate uncertain factors related to mold-manufacturing characteristics, the fuzzy theories developed by Zimmermann [13], Hannan [14], and Yang et al. [15] are also implemented. The specific objectives of this work are as follows: 1. analyze the factors crucial to mold-outsourcing strategy; 2. develop a cost-effective model for evaluating manufacturing capability and outsourcing capabilities; 3. generate a fuzzy multi-objective model that incorporates contracted objects; and 4. assess the applicability of different fuzzy theories. The remainder of this paper is organized as follows. Section 2 presents a literature review. Section 3 formulates the mold-production and outsourcing-decisions problem as a linear programming (LP) model with fuzzy multi-objectives. Section 4 tests and compares the applicability of the proposed methodology with different fuzzy theories using a case study of a mold-manufacturing firm. Section 5 gives conclusions and recommendations for further research.

Taiwan's mold industry produces high value-added molds and its technical level is high; however, pollution and energy consumption adversely impact. Mold-manufacturing firms must enhance value-added products by improving their technical capabilities. Investments to achieve high precision, high speeds, and high reliability are essential to competitive advantage. As products vary and their life-cycle is shortened, collaboration in development of outsourcing alliance and manufacturing is needed, and an appropriate mathematical model for evaluating cost-effectiveness is essential. A firm defines outsourcing inventions associated with manufacturing activities as competitive advantage, which obviously ignores the complex complicated production processes used by the mold industry. Thus, mold-manufacturing firms must apply feasible strategies to enhance supply chain efficiency and minimize production losses. Thus, mold-manufacturing firms require an alternative analytical model that considers how the cost-effectiveness of capacity planning is affected by outsourcing factors. The cost-minimization models with fuzzy multi-objectives in this study demonstrate the effectiveness of various solutions to mold production planning under varying application circumstances. The proposed FMOLP model tests the applicability of three different fuzzy set theories under continuous and discrete membership functions by implementing the case of mold-manufacturing firm in Taiwan. The novel features of the three models are their applicability for integrating capacity planning and outsourcing selections in terms of such factors as punishment costs and crashing costs. Satisfaction is also assessed to account for the imprecision of factor variation results when used for decision-making. Implementation results demonstrate that the application of MOLP model can optimize outsourcing alternatives. However, based on empirical results, the feasibility of this method requires further investigation. The fundamental obstacle to implementing this methodology is the interactions among multi-objectives. Although this work conducts a systematic analysis and presents potential solutions, additional data analysis is needed to implement the proposed FMOLP method.