Product manufacturing cost estimation in the early stages of the design process is useful for accelerating product time to market, reducing costs, and increasing quality in order to obtain products with a high level of competitiveness in the free market. Complexity and machining cost are important variables to estimate the final cost of the product. However, current cost estimation models only consider their calculations based on the design which has been determined beforehand, so that it is difficult to apply a cost estimation model early on in the design process because of minimal information. Therefore, in this research, a new method to produce a cost estimation model during the early stage of the design process is proposed. The new model was developed by correlating the cost calculation with the complexity of the machining process based on product features. By using this model, the designers are able to put through design changes quickly by modifying revisions at the manufacturing stage. In this paper, the development and implementation of the proposed cost estimation model which involves the milling process is known as the SPMF (Single Product Multi-Features) Product model is explained in detail. The proposed method shows that the SPMF Product model can be used to produce a manufacturing cost estimation based on process complexity.
Previous research has emphasized the need to further investigate the impact of manufacturing complexity on company strategies and performance in developing countries' manufacturing sector. Indonesia is one such developing country where this relationship has yet to be adequately studied. The manufacturing industry sector is expected to drive Indonesia's economic growth to achieve the targeted average growth of 6% per year in the next five years. This study aimed to examine the relationship between manufacturing complexity, manufacturing strategies (cost, delivery, flexibility, and quality), and manufacturing performance of Indonesian automotive component manufacturing industries. Partial least square structural equation modeling (PLS-SEM) was employed in the investigation. The sample size comprised 72 automotive component manufacturing companies located in the Jakarta region. Results indicated that the higher the value of manufacturing complexity, the higher the manufacturing strategies should be prioritized. The manufacturing strategy related to quality, particularly, has a significant positive impact on manufacturing performance. The novelty of this study lies in its detailed examination of the relationship between manufacturing complexity, manufacturing strategies, and manufacturing performance, particularly in developing countries. The results are expected to fill the existing research gaps.
It is a phenomenon that an experience mechanical/ design engineer with years of experience in mechanical parts design, still must to improve the knowledge about process design. This phenomenon will be different with other fields but common in process design because design is continuous process. The automotive industry is expected to be one of the driving factors for economic growth in Indonesia in 2025. It is shown by research firm (Frost & Sullivan) that estimates this year's car sales in Indonesia will rise moderately by 6.5% from a year earlier to 948,500 units and the real car sales in Indonesia rose to 43% in April 2012. Development should be increased because the government provides to industrial facilities that conduct research, development and innovation. Therefore the design process until production is expected to be rapid and immediate product can be enjoyed by society. To speed up the production process, the design process should be faster, and account how the next process that is the production. This research useds the form of the usual features carried with three machining processes are widely used in the world of mechanical component industries. The processes are turning (around 24.9% of machining process), milling (around 20.2% of machining process) and drilling (around 28.2% of machining process). The overall mean of the three processes around 73.3% of the portion of the machining process (survey conducted by PERA).
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