Md. Yusof Ismail

Loss-based process capability indices: a review

Process capability indices (PCIs) are appropriate tools to measure the inherent capability of a process, but most of them do not consider the losses of a process, while in todays competitive business environment, it is becoming more and more important for companies to evaluate and minimise their losses. This paper presents a review of loss-based PCIs such as Cpm, Cpmk, PCIθ, Cpc, Le and L″e. This paper also discusses characteristics of loss-based PCIs such as reject based, asymmetric, bounded, loss based and target based. Finally, recommendations were made for developing a new loss-based process capability index with more excellent specifications.

A New Technique to Measure Process Capability with Taguchi Loss Functions

Purpose of this study is to define a novel process capability analysis regarding to loss function. Loss functions such as Taguchi loss functions, assess the process losses, but this function do not distinguish real harmful loss. So in this study an improved Taguchi loss function method is constructed. Then regarding to this new function a novel process capability is developed. The logical idea is to use improved Taguchi quality loss function in order to measure the process capability. Main findings are improved Taguchi loss function that is more sensitive to losses and new process capability index base on improved Taguchi loss function, for qualitative response data, to evaluate the process capability for the qualitative response data.

Contribution of lean and Six Sigma to effective cost of quality management

In todays competitive market, most of the organisations promote quality as a critical success factor to achieve sustainable competitive advantages when the high quality of delivered product and service is considered extensively by the customers as a vital factor besides a reasonable price. Hence, most organisations would invest a lot of money to achieve the desired quality, at the same time, set a competitive price. Although, various quality improvement models, methods and tools can be applied to determine the most effective areas and the level of investment needed to measure, control and manage the cost of quality (COQ). This paper tries to present and summarise COQ models to identify COQ elements by emphasising the optimal quality cost model to see how lean and six sigma approaches can contribute to achieve further improvement in terms of reducing waste, time, defects and variation while targeting and obtaining the minimum total quality costs.

Overcoming the Challenges of Implementating Six Sigma in Service Industries

Six Sigma has been a powerful and successful tool in manufacturing industries to reduce rate of rejects and to enhance productivity. The service industries are diversified and the features are different from manufacturing industries. Thus, the use of Six Sigma in service industries and its benefits are limited to some specific types of services like health care and banks. This paper focuses on key performance indicators of Six Sigma and elements to cover a wider range of services. From the analysis of the service models, service industries structures and also by comparing between the features of service and manufacturing industries, the main challenges in application of Six Sigma in service industries can be identified. Further analysis of these challenges showed that the proper implementation of Six Sigma in service industries requires not only the effective operational strategies, but also customers’ needs and satisfaction must be considered and designed into the implementation phase. The paper proposed that for the successful implementation of Six Sigma in service industry, instead of just DMAIC, a design phase should be included (DDMAIC). The main meaning of this new phase and its affection will be described.

Process Capability Analysis Using Monte Carlo Simulation

Many process capability indices have been proposed to measure process performance and sometimes companies do not know which process capability index is more sensitive and suitable. One of the main points of process capability indices is how much they take into account process variability, departure of the process mean from the target value, and proportion of nonconformity (loss). In this paper, we first review Cp, Cpk, Cpm and Cpmk. Then we illustrate a comparison among process capability indices. In order to compare them appropriately, random data are generated by Monte Carlo simulation and besides the calculation of process capability indices, losses of process are calculated with Taguchi loss function. The results show that in point of view of departure of the process from the target value, these process capability indices are same and in point view of variability, Cpk are more sensitive.

TOPSIS for solving multi-objective multi-product supplier selection problem under price breaks

Supplier selection is a multi-criteria decision-making problem (MCDM) that is affected by quantitative and qualitative (conflicting) factors. For supplier selection problem, if suppliers offer quantity discounts and buyer wants to buy multiple products as well, this problem becomes more complicated. To solve the problem, an integration of technique for order preference by similarity to ideal solution (TOPSIS) and multi-product multi-objective mixed integer linear programming (MOMILP) is used to consider both tangible and intangible factors in choosing the best suppliers and define the optimum quantities among the selected suppliers. The problem includes the three objective functions: to maximize the total value of purchasing (TVP), and to minimize the total defect rate and total cost, while satisfying demand requirement and capacity constraints. In this paper, to solve the multi-objective model, TOPSIS and later a single objective function are proposed which can consider the relative importance of the three goals.