Quality costing: a management review

This paper relates a review of the English language literature on quality costing and traces its historical development; it provides authoritative reading on the subject. The review also has a focus on collection and use of quality-costing methods, quantitative cost data and the role and views of accountants in the task of quality-cost collection and reporting. Amongst the main findings is the preoccupation with the prevention – appraisal – failure categorization of quality costs and lack of guidance on definitions. The considerable impact of the American quality profession on the development of quality costing is pointed out along with the increasingly positive stance of accountants.     

Examining the Impact of Speed of Quality Improvement on Quality-Related Costs

The Fine (1986) quality-based learning curve model is extended to include the consideration of speed of quality improvement. The model demonstrates that under different circumstances rapid quality improvement effects are either beneficial or detrimental to improvement in quality-related costs. Hypotheses are developed from the analysis of this speed of quality improvement model. The hypotheses are tested in an automotive parts manufacturing company with five similar plants. Results show that with an increase in the speed of quality improvement, the rate of growth in prevention and appraisal costs decrease and the rate of growth in failure costs are unaffected. Rapid speed of quality improvement does yield lesser decreases in failure costs than slower, steadier improvement. However, rapid speed of quality improvement does not yield the predicted lesser decrease in prevention and appraisal costs than slower, steadier improvement. Rapid speed of quality improvement might or might not benefit the organization, perhaps an explanation for some Total Quality Management (TQM) failures. A more deliberate, learning organization is suggested from this research.     

From QA to TQM

In the decade from 1950 to 1960, two quality-related processes--medical audit and total quality management--were being developed, one directly in the health care field and the other in the manufacturing sector. These processes remained isolated from each other until the mid-1980s. Each would have a separate but major effect on the health care industry.     

ON-LINE QUALITY MANAGEMENT: INTEGRATION OF PRODUCT INSPECTION AND PROCESS CONTROL

A growing recognition that quality management is an important factor in defining a firm's competitive position has led to renewed attention to this function and has resulted in implementation of elaborate systems for on-line quality control comprising product inspection and process control. Traditionally, these functions have been treated independently, with very little interaction. In this paper we examine, in detail, a scheme that integrates the two functions, and we demonstrate that such an approach can result in significant cost savings. The motivation for this work comes from our experience in a wafer fabrication facility that suggested that exchange of quality information between different stages of production could result in significant performance improvements. To illustrate this approach, we consider a specific environment characterized by a single-stage continuous production process whose status is monitored by an X̄ control chart. We assume that quality-related costs may be described as a function of the process output. This is analogous to Taguchi's quality loss function and may be interpreted as a generalization of conventional classification of process output as either acceptable or defective units. The integrative scheme essentially relies on utilization of the process status information (based on process control) in making product inspection decisions. For this system we derive a cost model and develop a solution procedure to determine optimal decision parameters. Limited computational results indicate that the scheme has significant potential for reducing quality-related costs.     

The effects of the warranty cost on the imperfect EMQ model with general discrete shift distribution

In this paper, we investigate the effect of the warranty cost on optimization of the economic manufacturing quality (EMQ). This is done for a deteriorating process where the production process shifts from the in-control state to the out-of-control state following a general discrete probability distribution. Once the production process goes out of control, the production process produces some defective items. The defective item cost includes reworking and warranty costs. Thus, in order to economically operate a production-inventory system with products sold under warranty, the tradeoffs among the production setup, inventory, and defective item cost, including the reworked cost before sale and the warranty cost after sale, needed to be analysed. This objective in this paper is to determine the production lot size while minimizing the total cost per unit of time per unit of time. Various special cases are presented. Two of them are extensions of results obtained previously in the literature. Finally, a numerical example is given which uses a discrete Weibull probability distribution. Sensitivity analysis of the model with respect to cost and time parameters is also performed.     

Adoption of just-in-time based quality assurance and purchasing practices

Feasibility of transforming purchasing and quality control operations from conventional to just-in-time (JIT) practices is discussed. The study is confined to the dock-to-stores area of an engine manufacturing plant. Components used in the study are selected from a representative sample of inventory classes, commodity groups and agreement types with vendors. A time/cost analysis is carried out for the components selected so as to evaluate the cost effectiveness of the conventional purchasing and quality control. Findings on savings in terms of inventory-related costs and inventory turnover through the implementation of JIT practices are reported. A transformation framework is then developed to determine the suitability of individual components for JIT based practices. Cases are presented to demonstrate the functioning of the framework.     

DYNAMIC INTERACTION OF PRICE AND DESIGN QUALITY FOR PRODUCTS WITH CONVEX PRODUCTION COSTS

Price and design quality define value for customers and are often used by firms to position products in the marketplace. Setting price and quality level on a new product for the first time and making appropriate changes over time to these variables to reflect changing conditions in the market requires careful coordination of design, manufacturing, and marketing variables. We present a control theoretic model to study the complex interaction among price, quality, and cost during the life cycle of a product. Our model considers the major design-manufacturing-marketing tradeoffs and helps determine optimal pricing, design quality, and production strategies in a dynamic environment with convex production costs.     

MODELS FOR OPTIMAL LEAD TIME REDUCTION

Most inventory and production planning models in the academic literature treat lead times either as constants or random variables with known distributions outside of management control. However, a number of recent articles in the popular press have argued that reducing lead times is a dominant issue in manufacturing strategy. The benefits of reducing customer lead times that are frequently cited include increased customer demand, improved quality, reduced unit cost, lower carrying cost, shorter forecast horizon, less safety stock inventory, and better market position. Although the costs of reducing lead times in the long term may be relatively insignificant compared with the benefits, in the short term these costs can have a significant impact on the profitability of a firm. This article develops a conceptual framework within which the costs and benefits of lead time reduction can be compared. Mathematical models for optimal lead time reduction are developed within this framework. The solutions to these models provide methods for calculating optimal lead times, which can be applied in practice. Sensitivity analysis of the optimal solutions provides insight into the structure of these solutions.     

The new production theory for health care through clinical reengineering: a study of clinical guidelines--Part I

Drucker writes that the emerging theory of manufacturing includes four principles and practices: statistical quality control, manufacturing accounting, modular organization, and systems approach. SQC is a rigorous, scientific method of identifying variation in the quality and productivity of a given production process, with an emphasis on improvement. The new manufacturing economics intends to integrate the production strategy with the business strategy in order to account for the biggest portions of costs that the old methods did not assess: time and automation. Production operations that are both standardized and flexible will allow the organization to keep up with changes in design, technology, and the market. The return on innovation in this environment is predicated on a modular arrangement of flexible steps in the process. Finally, the systems approach sees the entire process as being integrated in converting goods or services into economic satisfaction. There is now a major restructuring of the U.S. health care industry, and the incorporation of these four theories into health care reform would appear to be essential. This two-part article will address two problems: Will Drucker's theories relate to health care (Part I)? Will the "new manufacturing" in health care (practice guidelines) demonstrate cost, quality, and access changes that reform demands (Part II)?     

废旧产品再制造环境下的产品定价和再制造方式分配

原材料价格的不断上涨,使得制造企业开始通过废旧产品的回收和再制造来缓解制造成本的上涨.然而,制造企业可以采用较昂贵的技术生产与新产品无差异的再制造品,也可以采用较廉价的技术生产在低端市场销售的再制造品,不同的再制造方式会给制造商带来不同的利润;另一方面废旧品的边际回收成本随着回收率的上升而上升,使得制造企业必须小心选择废旧品的回收数量.文中构建了高端市场和低端市场之间存在需求的线性替代关系时,再制造品和新产品的定价问题,并在优化计算的基础上得到了成本结构对于最优利润、最优价格、最优回收率和不同再制造方式比重的影响.     

Decision support tool for lean product and process development

Lean and concurrent engineering (CE) are widely acknowledged business process improvement strategies. These strategies can improve processes, reduce costs, and cut waste enabling organisations to remain competitive. Lean manufacturing offers an enterprise-wide methodology that improves reliability and flexibility while reducing lead-times and inventory carrying costs. Companies in manufacturing and service sectors are focusing on integrating lean manufacturing methodology with other applications, so that, all their systems and processes are aligned. This article proposes a CE framework based on application of information technology and object-oriented methodology for lean manufacturing. This approach expected to give manufacturing companies an extra edge in today's competitive market. A case study is presented in this article to demonstrate the effectiveness of CE framework in a machine tool manufacturing company. CE practice was adopted for new products, to align the systems and processes of the company. Product development lead-time was found to decrease by more than 50% compared to similar development projects carried out by the company. The need for rework was found to be negligible and the development cost was reduced considerably.     

Cost of quality reporting: Some Australian evidence

The study explored the quality management practices, specifically addressing cost of quality reporting, of Australian manufacturers certified to AS/NZS ISO 9000. The findings suggest that firms have responded to the demands of the new manufacturing environment and have implemented quality management initiatives in an effort to gain a competitive advantage in the marketplace. The minority of respondents prepared cost of quality reports. For those firms reporting quality costs, the motivation was to identify high-cost problem areas. Firms not reporting quality costs cited lack of management support and the belief that quality was part of the firm's culture.     

AN EXAMINATION OF THE INDIRECT PRODUCTIVITY GAINS FROM QUALITY IMPROVEMENT

Recent theoretical work suggests that quality-improvement activities can yield significant indirect effects through process improvements and reduced factory congestion and confusion, benefits that are overlooked or hidden in most management accounting or cost of quality systems. Using time series data from two consumer durables manufacturing plants, I estimate the indirect productivity gains from quality improvement. The evidence from the plants indicates that the indirect effects from improved quality are at least two to three times the direct benefits attributable to lower scrap, rework, and inventory holding costs. An important implication of these findings is that companies that justify investments and measure performance based only on the direct costs of poor quality will motivate managers to make suboptimal decisions regarding quality-improvement activities.     

A new MRP/GT lot sizing heuristic: A simulation study

This paper studies the lot-sizing problem in Material Requirements Planning/Group Technology (MRP/GT) systems. A GT production cell is designed to produce many families of components. A major setup is required when switching from manufacturing one family of components to another family, and a minor setup is needed when switching from manufacturing a component type to another component type within the same family. Inventory holding cost is incurred if inventory level is positive, and inventory shortage cost is incurred if inventory level is negative, that is, backordering. The objective of the proposed lot-sizing problem is to minimize the sum of major and minor setup costs, holding and shortage costs, and regular production cost, and to meet simultaneously the demand requirements. The proposed problem is modelled into a linear integer program, a heuristic method to solve the problem is proposed, and a simulation experiment conducted to evaluate the performance of the proposed heuristic and some existing heuristics. The computational results show that the proposed heuristic is useful to reduce the total cost significantly over a wide variety of simulated environments.     

EXPLAINING PLANT-LEVEL DIFFERENCES IN MANUFACTURING OVERHEAD: STRUCTURAL AND EXECUTIONAL COST DRIVERS IN THE WORLD AUTO INDUSTRY

Using data from 62 automobile assembly plants worldwide, we examine the extent to which various structural cost drivers (plant scale, automation, and product mix complexity) and exe-cutionalcost drivers (product manufacturability, management policies, and production practices) account for plant-level differences in manufacturing overhead. Our analysis of structural drivers finds that overhead hours per vehicle are negatively associated with production volumes, consistent with economies of scale in overhead functions. However, automation appears to have little influence on overhead levels. Product mix complexity's effect on overhead requirements varies with the complexity's form and the plant's manufacturing capabilities. Option and parts complexity (measures of peripheral and intermediate product variety) both exhibit adverse effects on overhead, reflecting the considerable logistical, coordination, and supervisory challenges that accompany an increased number of parts and more complex manufacturing tasks. In contrast, model mix complexity (a measure of fundamental variety) appears to have little impact on direct or overhead labor requirements in auto assembly plants. Our analysis of executional drivers provides empirical support for the claim that advanced manufacturing practices such as the reduction of buffers, multiskilled production workers, and the use of teams can lower overhead costs. We also find preliminary evidence that the lower overhead costs in Japanese auto assembly plants are due primarily to the use of multiskilled work teams and the shifting of traditional overhead activities to production workers. Overall, our results indicate that manufacturing overhead is a function not only of the structural cost drivers that have dominated the academic literature but also of executional cost drivers that are harder to duplicate and therefore potentially more valuable for achieving competitive advantage.     

带工期指派的产品服务系统订单随机调度问题研究

针对由一个制造工厂和多个区域服务中心组成的服务型制造企业,研究了考虑生产时间和服务时间均具有随机性且工期可指派的产品服务系统（PSS）订单调度问题。首先以最小化订单提前、误工和工期指派费用的期望总额为目标构建问题的优化模型,然后分析目标函数近似值的最优性条件,据此提出加权最短平均生产时间排序规则,并结合该规则与插入邻域局部搜索设计了启发式算法对问题进行求解,最后通过数值仿真验证算法的可行性和有效性。研究表明,提前费用偏差对PSS订单调度与工期指派决策的影响很小,因此企业管理者无需准确估计库存费用也能制定出比较有效的PSS订单调度策略;而工期指派费用偏差对决策结果的影响非常大,因此企业管理者在决策时必须谨慎估计该项费用。     

An Empirical Investigation of Costs in Batching Decisions*

This paper examines the use of costs and cost functions to model lot‐sizing decisions in batch manufacturing. The cost functions used to model a wide variety of manufacturing systems are typically derived from average cost models of unconstrained inventory problems. The use of setups and average inventories as the basis for modeling the economics of a typical batch manufacturing cell is shown to be inadequate. An alternative physical model that focuses on lead times provides a model that more closely represents the underlying value of such a cell.     

The Effect of Misclassification Costs on Neural Network Classifiers

The potential of neural networks for classification problems has been established by numerous successful applications reported in the literature. One of the major assumptions used in almost all studies is the equal cost consequence of misclassification. With this assumption, minimizing the total number of misclassification errors is the sole objective in developing a neural network classifier. Often this is done simply to ease model development and the selection of classification decision points. However, it is not appropriate for many real situations such as quality assurance, direct marketing, bankruptcy prediction, and medical diagnosis where misclassification costs have unequal consequences for different categories. In this paper, we investigate the issue of unequal misclassification costs in neural network classifiers. Through an application in thyroid disease diagnosis, we find that different cost considerations have significant effects on the classification performance and that appropriate use of cost information can aid in optimal decision making. A cross-validation technique is employed to alleviate the problem of bias in the training set and to examine the robustness of neural network classifiers with regard to sampling variations and cost differences.     

A low-cost approach to computer-integrated manufacturing in a small chemical unit

Many firms are considering CIM as a means of reducing costs and increasing quality. Sometimes, however, a major problem in this kind of project seems to be the high investments involved. In this paper a methodology for developing a low-cost CIM application is presented. The proposed methodology was successfully experimented in a small chemical unit of one of the leading producers of nylon in the world. The paper reports on the design and implementation of the computer-integrated manufacturing and the associated costs and benefits.     

Stockout risk of production-inventory systems with compound Poisson demands

Production-inventory systems with continuous production or continuous manufacturing have been implemented in a variety of manufacturing contexts. Most recently, the Commissioner of the FDA has called on drug and biological product manufacturers to begin switching from batch manufacturing processes to continuous production. Motivated by prevailing applications and the emerging and promising landscape in the healthcare and pharmaceutical industries, this paper studies a continuous-review production-inventory system with a constant production rate and compound Poisson demands, in which the cost of the system is assessed via inventory holding, stockout penalty and production costs. For any initial inventory, we derive a closed-form expression for the expected discounted cost function until stockout occurrence. We systemically quantify the stockout risk on four different dimensions (i.e., time, volume, frequency and percentage) and derive explicit expressions for each type of risk metric. The objective is to derive the production rate that minimizes the expected discounted system cost subject to a given risk tolerance level on stockouts. With the aid of the derived explicit forms of stockout risk and the cost function, we develop a computationally-efficient algorithm for the optimal solution. Extensive numerical studies are conducted to illustrate our results with rich insights. Numerically, we show that it is outrageously costly to reduce stockout risk, especially when this risk is relatively low; the value of risk is more sensitive to the stockout risk level if the demand distribution has a higher volatility.