Performance-based costing as decision support for development of discrete part production : Linking performance, production costs and sustainability

TL;DR: In this article, the authors present a cost model for discrete part manufacturing, which is a time-based technical performance-based cost-model for discrete parts manufacturing, incorporating performance parameters such as cycle time, quality rate, process material waste, speed losses, availability losses, set-up times, and degree of capacity occupancy.

Abstract: In today’s global market, the industry is struggling every day to make the “correct decisions”. Decisions concerning production can range from smaller improvements to choice tool or equipment investments to relocation of entire production facilities. Increasing globalization leads to both opportunities and challenges, driving the need for fact-based decision-support including costs to be able to evaluate the cost outcome of different production development alternatives. For a high cost country, such as Sweden it is important to continuously increase productivity to counterbalance the high cost of labour, taxes and services. A trend, that has existed for several decades, is to relocate manufacturing to countries with lower costs, especially with lower labour costs. Production relocation often results in higher initial costs, which makes it essential to make the correct decision from the beginning.To ensure that the production is in line with manufacturing strategy, performance measurements are commonly used. Measurements/indicators can also be used to make strategy more tangible, facilitating information and knowledge transfer. In other words, they can be used to inform co-workers about how the company is doing and how the system and processes respond to different actions. Interactive use of a performance measurement system and frequent analyses of indicators can be conducted to generate learning about actions leading to higher performance.Recent movements within the industrial sector point towards increasing efforts to take responsibility for the environment. However, cost savings are one of the prominent drivers for sustainability improvements, together with governmental legislation, market advantages, and pressure from shareholders and stakeholders. Prominent obstacles for sustainability improvements have been found to be a lack of understanding and knowledge, unclear and fuzzy decision authorization, and lack of performance measurements are noticeable reported reasons. The traditional cost method, involves direct material, direct labour, and overhead costs. When the costing method was implemented, a large proportion of the production cost consisted of labour costs, but as the equipment complexity and equipment costs increase the need for more detailed cost-models arises. One of the major goals in this thesis is to use knowledge of performance and capability in production operations to support decision on future developments and configurations. Therefore, it is important that the cost-model used captures as many aspects as possible and, especially performance parameters. The cost-model used in this thesis is a time-based technical performance-based cost-model for discrete part manufacturing, incorporating performance parameters such as cycle time, quality rate, process material waste, speed losses, availability losses, set-up times, and degree of capacity occupancy. Research has been conducted within cost-conscious manufacturing addressing cost impact on production decisions such as production location, automation level, product cost consequences of alterative equipment resources, energy consumption, and sustainability. The aim of this thesis is to provide decision-makers with structures for information gathering from the production system in order to make sound short-term and long-term tactical and strategic decisions incorporating production performance. The research contribution can be divided into four parts: 1) Cost-model applications for specific analyses and decisions. 2) Cost model development, adding aspects of material handling and tied-up capital to develop the manufacturing cost-model into a production cost-model. 3) Support location decisions with a cost-based decision framework. 4) Support sustainable production using a production performance-based costing perspective. (Less)