Non-conformance Costs Research Articles

The economic production quantity model with optimal single sampling inspection

Abstract This paper derives an inspection policy for an economic production quantity (EPQ) model under the assumption that a process may produce non-conforming (NC) items. In various stages of a production process, a department receiving an order uses a single sampling inspection policy to detect NC items. Under such a policy, a lot is accepted if the number of NC items in the inspected sample is equal to or less than the acceptance number. The proposed model considers both EPQ- and quality-related costs. Moreover, economic production order quantity, sample size and acceptance number are considered decision variables. A numerical example is presented, and a set of sensitivity analysis are provided to highlight the effectiveness of the proposed model. The results reveal that when the inspection cost is high, the classical EPQ model achieves a lower expected total cost for the production system compared with the EPQ model with the inspection. In contrast, when the NC cost is high, the EPQ model with the inspection policy outperforms the classical EPQ model, which can significantly decrease the expected total cost.

The joint determination of process mean, quality investment, replenishment cycle time, and credit period for the integrated supply chain model

In this work, the authors proposes the modified Banu and Mondal’s model for obtaining the optimal process mean, quality investment, replenishment cycle time, and trade credit period. Assume that the product quality is normally distributed with unknown process mean and known standard deviation. The product is considered under the larger-the-better characteristic. The declining exponential reduction of process standard deviation is the function of quality investment. Numerical results show that (1) the production cost per item and the parameter of quality investment function for the process standard deviation have the effect on the process mean; (2) the production cost per item, the non-conforming cost per item, the parameter of quality investment function for the process standard deviation and the known process standard deviation have the major effect on the quality investment; (3) the production cost per item has the effect on the retailer’s replenishment cycle time; (4) the production cost per item has the major effect on the expected total profit including the manufacturer and the retailer per unit time.

A Maintenance Model Applying Loss Function Based on the Cpm+ in the Process Mean Shift Problem in Which the Production Volume Decreases

Machines and facilities are physically or chemically degenerated by continuous usage. The representative type of the degeneration is the wearing of tools, which results in the process mean shift. According to the increasing wear level, non-conforming products cost and quality loss cost are increasing simultaneously. Therefore, a preventive maintenance is necessary at some point . The problem of determining the maintenance period (or wear limit) which minimizes the total cost is called the ‘process mean shift problem’. The total cost includes three items: maintenance cost (or adjustment cost), non-conforming cost due to the non-conforming products, and quality loss cost due to the difference between the process target value and the product characteristic value among the conforming products. In this study, we set the production volume as a decreasing function rather than a constant. Also we treat the process variance as a function to the increasing wear rather than a constant. To the quality loss function, we adopted the Cpm+, which is the left and right asymmetric process capability index based on the process target value. These can more reflect the production site. In this study, we presented a more extensive maintenance model compared to previous studies, by integrating the items mentioned above. The objective equation of this model is the total cost per unit wear. The determining variables are the wear limit and the initial process setting position that minimize the objective equation.

Perspectives on the adherance to scrum rules in software project management

Adapting users need to fulfill their requirements and delivering products to be on time within the planned cost, is critical matter that all software project managers (SPM) put the highest priority for it while considering the users satisfaction at the same time. Agile methodology is one of the solutions provided by software engineers (SE), to get the customers involved in the system development life cycle (SDLC) to avoid the risk nonconformance cost. Yet SPM’s still facing the nonconformance costs and the dynamic changes, and the root cause of the issue is not pointed on to find a solution for it. This undertaking research aimed at determining whether software developers understand scrum rules. In addition, how does this knowledge gab affect the software projects success from the project management perspective. Furthermore, the engagement studied the impact of lack of enough knowledge on the topic to project delivery. The collected data from the qualitative and quantitative methods, which was conducted with scrum teams who worked in the <span>health information system</span> (HIS), Educational solutions, and Governmental solutions has showed deviations in organizational practices and team conflicting, competition, and pressure as well as declined product quality.

Quality infrastructure services capability assessment in the coffee value chain

Coffee generates about 25%-30% of total export and securing about 15 million people's livelihoods in Ethiopia. But, it has several quality issues. Studies show a total of 272 million USD of which 99% is due to the non-conformance cost of the export product incurred annually. This justifies mitigating quality problems in the sector is important. Therefore, to deal with this issue coffee quality related data were collected from Ethiopian National Quality Infrastructure Institutions (ENQI) and Coffee Quality Inspection and Certification Association (CLU). Eighteen experts purposively selected from both institutes were asked to associate quality service with defects. Finally, lack of accreditation has the highest contribution followed by conformity and metrology with a share of 83.3%, 75%, and 54% for defects points. Moreover, issues like control of temperature and humidity in storage and transport, lack of soil nutrition testing, inspection performance, and commitment to standards implementation are issues that needs to be improved.

Determination of the Wear Limit to the Process Mean Shift Problem with Varying Product and Process Variance

Machines and facilities are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. The representative type of the degeneration is wear of tool or machine. According to the increasing wear level, non-conforming products cost and quality loss cost are increasing simultaneously. Therefore a periodic preventive resetting the process is necessary. The total cost consists of three items: adjustment cost (or replacement cost), non-conforming cost due to product out of upper or lower limit specification, and quality loss cost due to difference from the process target value and the product characteristic value among the conforming products. In this case, the problem of determining the adjustment period or wear limit that minimizes the total cost is called the ‘process mean shift’ problem. It is assumed that both specifications are set and the wear level can be observed directly . In this study, we propose a new model integrating the quality loss cost, process variance, and production volume, which has been conducted in different fields in previous studies. In particular, for the change in production volume according to the increasing in wear level, we propose a generalized production quantity function g(w). This function can be applied to most processes and we fitted the g(w) to the model. The objective equation of this model is the total cost per unit wear, and the determining variables are the wear limit and initial process setting position that minimize the objective equation.

A solution to reduce overheating and increase wind turbine systems availability

The ever-increasing demand for electrical power and the tremendous growth of renewable energy sources in the past decade has led designers to design wind turbine system components for optimal performance. Cost optimization, weight reduction, higher performances, and lower non-conformance cost are a few expectations that components are expected to meet in the present market condition. Wind turbine system unavailability impacts the annual energy production of the wind turbine. Overheating of the wind turbine system components is one of the main challenges to overcome. For the heating analysis, we discuss the wind turbine generator as a specific example in this article. This approach is equally valid for other components of wind turbine systems, with heat exchanger. Windings and bearings are the two main components susceptible to failure in the generator for wind turbine applications. The root cause may vary from case to case, but overheating accelerates the generator’s windings and bearing failure and in many cases is the prime reason behind. Running the components at higher load points is one of the reasons for components to overheat. The article presents a solution to improve the performance of the wind turbine system and at the same time making it a commercially attractive choice. This can be achieved by reducing generator windings and bearings operating temperature, and also reducing its cost and weight at the same time. The proposed solution to reduce overheating is achieved and verified through results. The achieved results also explain how one solution is advantageous over the other.

Determination of the optimal blending problem of organic‐chemical fertilizer under uncertainty

AbstractThe advantages of organic‐chemical fertilizers have been recognised by farmers, and accordingly, the demand for them has increased. An organic‐chemical fertilizer, with an amount of nutrients less than that registered or as specified on the label, is considered a fake or a nonconforming fertilizer. It has been observed that nutrient compositions of samples of organic‐chemical fertilizers are much greater than what is specified on the label. This research aimed to reduce the raw materials cost of organic‐chemical fertilizers while increasing the conformance probability of the nutrient composition. Three models have been formulated to determine the optimal organic‐chemical fertilizer blend: a linear programming model (LP), a chance‐constrained programming model (CCP), and a simulation optimization model. A Monte Carlo simulation was developed to determine the probability that the blending formula, currently in commercial use, and blending formulas obtained from the three optimization models, would be out‐of‐specification. The current and three proposed models were compared in terms of total raw material cost and probability of nonconformance. Our blending formulas could save a material cost of at least 16.6% compared with the commercial formula. Also, the probability of producing nonconforming fertilizers is drastically reduced. On a macro level, the use of the models allows farmers to reduce chemical residues in the soil while Thailand could reduce the import volume of chemical substances. This research may have a significant impact on manufacturers, farmers and the Thai economy.

A grey mathematical model for crashing of projects by considering time, cost, quality, risk and law of diminishing returns

PurposeThe purpose of this paper is to examine projects crashing based on the factors including cost, time, quality, risk and the law of diminishing returns.Design/methodology/approachThe paper first investigated effective factors on project crashing then proposed a grey linear programming model. In the proposed grey linear programming model, the costs of quality of works that include the cost of conformance and non-conformance of deliverables in the project were studied. The results are presented for considering the existing uncertainties using positioned programming under the sensitivity analysis table and graphs.FindingsThe lack of consideration of project risks will reduce the project success probability in future. The proposed model reduces the existing uncertainties to a significant extent by covering the project risks completely. Based on the law of diminishing returns, after a certain point technically known as saturation point, the increase of resources does not lead to the reduction of time and may even have negative impacts. Finding the saturation point for each activity prevents the excessive allocation of resources that can lead to reduction of productivity.Practical implicationsThe main duty of each project manager is finishing the project in the framework of the determined objectives. In most of the cases, after the preparation of the initial project schedule by the project team, it is seen that there is a need for the time reduction. This study has used a grey linear programming model for optimum crashing of project activities. In order to make the model more realistic and applicable, the authors endeavoured to consider most of the factors that are involved in doing a project.Originality/valueIn the present study, to the best of the authors’ knowledge the factors of time, cost, quality, risk and the law of diminishing returns are simultaneously considered in project crashing for the first time and the grey theory was used for considering the uncertainties of project parameters. Also, “the law of diminishing returns” has not been considered during crashing in the studies conducted so far.

A new economic scheme for CCC charts with run rules based on average number of inspected items

ABSTRACTNew statistical techniques and procedures have been developed to control high-yield processes along with looking for process improvement opportunities and minimizing production cost. Cumulative count of conforming control chart is generally a technique for high-quality processes, when nonconforming items are rarely produced. The objective of this study is to design control chart based on cumulative count of conforming items and run rules that develops an economic model based on the average number of inspected items to design m-of-m CCC chart in order to facilitate minimum average cost per item produced. The optimal design parameters for different values of nonconforming fraction and different cost parameters in each scenario are determined. Finally, to analyze the behavior of optimal economic solutions, sensitivity analysis of the model parameters is performed.

National cost of quality in Ethiopian import–export

Measuring and controlling cost of quality (CoQ) at the organisational level help us to know how poor quality negatively affects customer satisfaction. It would then be easy to see its effect if measured at the national level. But up to now, no effort has been made to measure CoQ at such a high level. The aim of this study is to analyse national cost of quality (NCoQ) by taking the Ethiopian import–export market as a case in point. Five years’ data regarding these two types of quality cost of imported and exported products were collected from reliable public institutions. The NCoQ is measured based on Crosby's method of determining CoQ which basically constitutes the conformance and nonconformance costs. The findings of the study showed that about 272 million US dollars are incurred every year due to quality problems only in the Ethiopian import–export sector, of which more than 99% was incurred due to the nonconformance cost of export products. All conformance costs have been estimated to be only less than 1% of the nonconformance costs. It has also been found that nonconformance CoQ in Ethiopian export is estimated to be about 41% of the total export value of the country. The analysis and measurement made in this study show the severity of nonconformance costs and the importance of investing in quality conformance.

Kosten und Nutzen eines Qualitätsmanagements

The establishment of quality management (QM) has been mandatory for health care providers of the national health insurance since 2004; however, certification is so far only compulsory for rehabilitation clinics. The costs have so far only been quantified in a few medical studies, while they are widely known in business administration with a basic distinction made between planning, steering, auditing, and declaration costs. Another business economics approach differentiates between prevention, appraisal, and non-conformance costs. The benefits of QM relates to customers, employees, external service providers, and health insurance providers. Also important in our consideration of the patient as a customer is that they should not be considered a customer in the usual business sense because the patient is in an emergency situation and can not freely decide. Improvements in treatment quality and in reducing the rate of adverse events make up the largest portion of the benefits of QM. Furthermore, QM can have a positive influence on motivation and employee recruitment. In addition, the cost savings that result despite costs for QM must not be forgotten.

Economic-statistical design of EWMA-3 control chart for monitoring simple linear profiles

In this paper, the EWMA-3 control chart for monitoring simple linear profile is economic-statistically designed. Average run length criterion of the EWMA-3 control chart is computed by using a Markov chain approach. In the proposed model, the Lorenzen and Vance cost function is applied and the parameters of non-conforming production cost are computed based on the Taguchi cost function. The proposed model is solved by a genetic algorithm. Finally, a sensitivity analysis is done on the parameters of the proposed model.

Determining the production lot size with a heuristic inspection policy for controlling the quality of input materials and products

This study simultaneously determines the optimal production lot size and an inspection policy for input materials and products, where an unreliable process produces products with a discrete general shift distribution. This work proposes a heuristic inspection policy for materials and products, by first obtaining the inspection range for the input material without considering product inspection, and by further determining the product inspection range based on the obtained range of the input material inspection. The optimal inspection policy shows that common policies of no or full inspection are never optimal. This study includes the optimal production lot size based on the obtained inspection policy. Numerical examples demonstrate the impacts of input quality level, process reliability and unit nonconforming cost on the optimal solution, which adopts a discrete Weibull shift distribution to model the process failure time. Finally, this study addresses the conclusions.

Designing the optimal mean for an asymmetrically distributed process

In a manufacturing environment where concerns for product quality or excessive cost are often present, process optimisation is typically an engineering objective. One method that supports the reduction of nonconformance costs and loss in product quality is the identification of the optimal process mean. Given the specification limits and associated costs for a process, the traditional method uses assumed values for the process parameters to estimate the ideal location of the mean. In contrast, this paper proposes using a methodology that removes the need to make assumptions on the process parameters. Furthermore, while most research examines the role of the nominal-the-best characteristic in the design of the optimal process mean, this paper specifically looks at smaller-the-better and larger-the-better quality characteristics. The skew normal distribution, which is relatively new to engineering applications, is considered in modelling these characteristics. A non-linear programming routine with economic considerations is used to facilitate this study.

Quality in operational supply chain networks: an aerospace case study

Supply chain modelling is attracting the interest of many researchers and is a topic that has application in real-life management practices. In the aerospace industry, quality is an important factor and suppliers are chosen on the basis of quality as well as cost. By integrating cost of quality (COQ) into supply chain network design (SCND), managers could make decisions based on operational costs and quality non-conformance costs. This paper presents a case study for a leading company in the aerospace industry with COQ integrated into SCND. Further in this paper, we present a model that tailors to a real-life supply chain with COQ, binary variables for assignable cost representation of supply chain nodes and an n level bill of material integrated; the model resulting is a non-linear model and is challenging to solve. A simulated annealing-based solution procedure is then used to solve the overall model.

ANALYSIS OF SEQUENTIAL MONITORING SCHEMES USING NATURAL CONJUGATE PRIORS

The complexity of modern manufacturing underscores the need for improved control strategies for these systems. We formulate a Bayesian attribute sequential monitoring plan useful for adaptive control of a production process. The Bayesian framework is based on natural informative conjugate priors that provide an optimal adjustment interval k in response to real-time changes in the operating characteristics of a process. The sampling and adjustment decisions are based on the tradeoffs between quality costs and quality parameters resulting from the process. The parameters include the fraction of nonconforming products p, and the number of nonconforming products r. The quality costs, which include the inspection, cost, repair cost, nonconformance cost, and adjustment cost are fixed and used to develop a breakeven relationship that that results in a sequential sampling construct that optimizes both the systems costs and process quality.

If prevention is better than cure, why do firms do the opposite?

Common wisdom tells that, regarding quality, prevention is better than appraisal. Although scholars and practitioners concur with that, firms in practice prioritise appraisal, leading to high non-conformance quality costs. To unravel this puzzle, we understand quality as the combined result of prevention, done by the firm's back office (e.g. production), and appraisal, done by the front office (e.g. marketing). We propose a game theoretic model for which quality expenditure is an equilibrium outcome that depends on the cost of technology, the customers' sensitivity to quality, and the distribution of (variable) incentives within the firm. We conjecture those conditions for the reported quality expenditures of several companies, and calculate their optimal quality investment policy. As advocated by experts, we find that prevention should more than double appraisal, and non-conformance costs should approach zero.

A research on the measurement of quality costs in the Turkish food manufacturing industry

The measurement of quality costs is a good indicator of the quality and the overall performance of a firm. There have been many attempts to measure quality costs in both theoretical and empirical research. However, there is a lack of research about the measurement of quality costs as far as the food industry is concerned. Therefore, the purpose of this study is to measure quality costs with specific reference to the Turkish food manufacturing industry. In contrast to many previous studies made with cross-section or time series regression, panel regression method has been used to analyse the relation between conformance costs and non-conformance costs in seven leading Turkish food manufacturing firms, for the period 2000–2005. It has been found that when the conformance costs are increased by 1%, the non-conformance costs decline by 0.83%. This also means that the basic premise of the traditional quality cost model has been confirmed. That is to say, there is a trade-off between conformance and non-conformance costs and the non-conformance costs can be reduced by increasing conformance expenditures. In conclusion, the negative relation found between conformance and non-conformance costs can rather be attributed to external failure costs than internal failure costs.

Optimising the Gaussian-distributed filling process parameters

A filling production system is that characterised by two contradicting nonconforming cost components. The first component is that incurred when the product specification exceeds the upper tolerance limit, called an overfill cost, whereas the second cost component is contributed when the product specification falls below the lower tolerance limit, called an underfill cost. The ratio of the two cost components affects to a high extent the choice of the process parameters, especially the process location parameter that minimises the overall costs. The work in this research is devoted to finding the filling process's optimum parameters; namely the process's mean and variance, considering a Gaussian-distributed process. Firstly, the process's variance is considered constant; and searching for the optimal process mean parameter takes place. An analytical, closed form, solution model is developed that realises such target. The developed model is ended up with a graph that can simply be used by concerned engineers and practitioners. The assumption of a constant process variance is then relaxed; and the developed model is extended to involve the variance reduction cost. An algorithm is introduced to solve the extended model that optimises the filling process' mean and variance.