International Journal of Industrial Engineering & Production Research

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 In this research, a new control policy for the acceptance sampling problem is introduced. Decision is made based on the number of defectives items in an inspected batch. The objective of the model is to find a constant control level that minimizes the total costs, including the cost of rejecting the batch, the cost of inspection and the cost of defective items. The optimization is performed by approximating the negative binomial distribution with Poisson distribution and using the properties of binomial distribution. A solution method along with numerical demonstration on the application of the proposed methodology is presented. Furthermore, the results of sensitivity analysis show that the proposed method needs a large sample size .

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  For any organization sound marketing strategy and quality assurance play vital role in the growth of the organization. The price, quality and service, service centers, friendly attitude, Discounts on sales, esthetics, store location and appearance, ease of operations, guarantees and warranties, adopting new ideas, and flexible payments terms were considered to study the perceptions of the respondents. The ultimate aim is to uphold the turnover of the organization and to create good market penetration of the goods produced in highly competitive business world .

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New home buyers in United States are becoming more discriminating in their home buying decision. They are demanding quality construction at reasonable prices. The current state of construction market also gives construction buyers more ammunition to be more discriminate when they choose to purchase homes.  To be competitive and remain in business, housing contractors and developers must meet the growing quality demands of the customers. Thus, the competition to meet the buyers’ quality demand has forced many of them to rethink the ways they build their homes. The improved designs, and construction methods and practices have resulted into award-winning quality-built homes for many of these contractors. This study was conducted to examine the quality improvement characteristics of selected award-winning residential builders and housing developers in selected counties in North Carolina, U.S.A.  Through a structured questionnaire, the researchers collected information relative to their common quality characteristics, organizational culture and overall business practices. Data analysis was performed using basic descriptive statistics. The results show that regular inspection of work in progress, feedback from customers, and immediate attention to punch list items, were highly ranked among the quality characteristics evaluated.

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Most of the researches in the domain of fuzzy number comparisons serve the fuzzy number ordering purpose. For making a comparison between two fuzzy numbers, beyond the determination of their order, it is needed to derive the magnitude of their order. In line with this idea, the concept of inequality is no longer crisp however it becomes fuzzy in the sense of representing partial belonging or degree of membership. In this paper we propose a method for capturing the membership degree of fuzzy inequalities through discretizing the μ-axis into equidistant intervals. It calculates m in the fuzzy inequalities ≤ m and ≥m among two normal fuzzy numbers. In this method, the two μ-axis based discretized fuzzy numbers are compared point by point and at each point the degree of preferences is identified. To show its validity, this method is examined against the essential properties of fuzzy number ordering methods in [Wang, X. and E.E. Kerre, Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Sets and Systems, 2001. 118(3): p. 375-385.] The result provides promising outcomes that may be useful in the domain fuzzy multi criteria or multi-attribute decision making analysis and also fuzzy mathematical programming with fuzzy inequality constraints.

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In this research, the decision on belief (DOB) approach was employed to analyze and classify the states of uni-variate quality control systems. The concept of DOB and its application in decision making problems were introduced, and then a methodology for modeling a statistical quality control problem by DOB approach was discussed. For this iterative approach, the belief for a system being out-of-control was updated by taking new observations on a given quality characteristic. This can be performed by using Bayesian rule and prior beliefs. If the beliefs are more than a specific threshold, then the system will be classified as an out-of-control condition. Finally, a numerical example and simulation study were provided for evaluating the performance of the proposed method.

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The paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. Some mathematical vector models were obtained for control system multicriterion quality indices with due consideration of stability and quality indices criteria, this increasing the reliability of optimal control system synthesis. Optimal control systems with fuzzy controllers were synthesized for nuclear reactor, steam generator and steam turbine, thus allowing comparison between fuzzy controllers and traditional PID controllers. Mathematical models built for nuclear power station generating unit control systems, including nuclear reactor, steam generator, steam turbine and their control systems interacting under normal operational modes, which permitted to perform parametrical synthesis of system and to study various power unit control laws. On the basis of power unit control system models controllers were synthesized for normal operational modes.

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There has been considerable number of papers published related to Six Sigma applications in manufacturing and service organizations. However, very few studies are done on reviewing the literature of Six Sigma in all the areas including manufacturing, construction, education, financial service, BPOs and healthcare etc. Considering the contribution of Six Sigma in recent time, a more comprehensive review is presented in this paper. The authors have reviewed Six Sigma literature in the way that would help research academicians and practitioners to take a closer look at the growth, development, and applications of this technique. The authors have reviewed various journal papers and suggested different schemes of classification. In addition, certain gap areas are identified that would help researchers in further research.

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Abstract Nowadays supply chain management has become one of the powerful business concepts for organizations to gain a competitive advantage in global market. This is the reason that now competition between the firms has been replaced by competitiveness among the supply chains. Moreover, the popular literature dealing with supply chain is replete with discussions of leanness and agility. Agile manufacturing is adopted where demand is volatile while lean manufacturing is used in stable demands. However, in some situations it is advisable to utilize a different paradigm, called leagility, to enable a total supply chain strategy. Although, various generic hybrids have been defined to clarify means of satisfying the conflicting requirements of low cost and fast response, little research is available to provide approaches to enhance supply chain leagility. By linking Leagile Attributes and Leagile Enablers (LAs and LEs), this paper, based upon Quality Function Deployment (QFD), strives to identify viable LEs to achieve a defined set of LAs. Due to its wide applicability, AHP is deployed to prioritize LAs. Also, fuzzy logic is used to deal with linguistics judgments expressing relationships and correlations required in QFD. To illustrate the usefulness and ease of application of the approach, the approach was exemplified with the help of a case study in chemical industry.

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Achieving optimal production cycle time for improving manufacturing processes is one of the common problems in production planning. During recent years, different approaches have been developed for solving this problem, but most of them assume that mean quality characteristic is constant over production run length and sets it on customer’s target value. However, the process mean may drift from an in-control to an out-of-control at a random point in time. This study aims to select the production cycle time and the initial setting of mean quality characteristic, so that the expected total cost, consisting of quality loss and maintenance costs as well as ordering and holding costs, already considered in the classic models is minimized. To investigate the effect of mean process setting, a computational analysis on a real world example is performed. Results show the superiority of the proposed approach compared to the classical economic production quantity model.

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The Multi-Mode Resource Constrained Project Scheduling Problem (MMRCPSP) is one of the most important problems in project scheduling context. The MMRCPSP consists of activities to be scheduled subject to precedence and resource constraints. The effort needed in order to accomplish activities in the MMRCPSP is a discrete function of job performing modes. However, MMRCPSP is a basic model with a rather too restrictive assumptions to be applied practically. Therefore, there are many extensions over basic MMRCPSP model in terms of objective functions, resource constraints, and solving procedures. This research is aiming at fulfilling tow ambitions. First, to collect researches related MMRCPSP and to classify them based on a framework consisting of six distinct classes. Second, to indicate current trends and potential areas of future research. In order to fulfill the second goal a new mathematical method is proposed and applied which identify recent trends and gaps in a systematic manner.
 

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Human-based quality control reduces the accuracy of this process. Also, the speed of decision making in some industries is very important. For removing these limitations in human-based quality control, in this paper, the design of an expert system for automatic and intelligent quality control is investigated. In fact, using an intelligent system, the accuracy in quality control is increased. It requires the knowledge of experts in quality control and design of expert systems based on the knowledge and information provided by human and equipment. For this purpose, Fuzzy Inference System (FIS) and Image Processing approach are integrated. In this expert system, the input information is the images of the products and the results of processing on images for quality control are as output. At first, they may be noisy images; the pre-processing is done and then a fuzzy system is used to be processed. In this fuzzy system, according to the images, the rules are designed to extract the specific features that are required. At second, after the required attributes are extracted, the control chart is used in terms of quality. Furthermore, the empirical case study of copper rods industry is presented to show the abilities of the proposed approach.
 

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Nowadays, competitive market creates the necessity of quality improvement in different levels of supply chains (SCs). This paper contributes to the SC coordination literature and proposes a bilateral coordination contract for optimizing pricing decisions along with quality improvement decisions in different echelons of a real case of a cell phone SC. The SC comprises a manufacturer who deals with determining the product quality, and a retailer who seeks for the optimal strategy on price, after-sale service and service level in a periodic review inventory system. The proposed bilateral wholesale price (BWP) contract is shown to be capable of simultaneous coordination of these decisions. The sensitivity analysis showed that in a market which is sensitive to quality and after-sale service as well as the product price, the proposed model facilitates investing more in such quality improvements while the members’ profitability with respect to the case without contracts is guaranteed. Moreover, it can increase the SC service level since it enables the members to hold more safety stock even under high inventory costs. Overall, the proposed coordination model on pricing, product quality, after-sale service and service level, leads to the optimal performance of the SC and its members while it is beneficial for the customers.

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Abstract
Background: In this paper healthcare condition of 31 countries that are the members of Organization for Economic and Co-operative Development (OECD) is measured by considering 14 indicators that are relevant to three main pillars of sustainable development.
Method: To estimate the efficiency scores, Principle Component Analysis-Data Envelopment Analysis PCA-DEA additive model in both forms of envelopment and multiplier is used to determine efficiency scores and also to define benchmarks and improvement plan for the inefficient countries. Then Decision Tree Analysis is also used to realize that which factors were the most influential ones to make a county an efficient Decision Making Unit (DMU).
Results: According to the PCA-DEA additive model, among 31 OECD countries, 16 countries have become inefficient, that USA have taken the lowest efficiency score, and among efficient countries Iceland could be considered as a paragon which has the highest frequency between the countries that are defined as the benchmarks. Decision tree analysis also show that exposure to PM2.5 is an influential factor on the efficiency status of countries.
Conclusion: This research gives an insight about the sustainable development and healthcare system and show the impressive effect of environmental and social factors like: exposure to PM2.5 and water quality, population insurance coverage, and AIDS on the healthcare efficiency of OECD countries

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One of the basic assumptions of classical production-inventory models is that all products are of perfect quality. However, in real manufacturing situations, the production of defective items is inevitable, and a fraction of the items produced may be naturally imperfect. In fact, items may be damaged due to production and/or transportation conditions in the manufacturing process. On the other hand, some reworkable items exist among imperfect items that can be made perfect by additional processing. In addition, the classical production-inventory models assume that there is only one product in the system and that there is an unlimited amount of resources. However, in many practical situations, several products are produced and there are some constraints related to various factors such as machine capacity, storage space, available budget, number of allowable setups, etc. Therefore, we propose new constrained production-inventory models for multiple products where the manufacturing process is defective and produces a fraction of imperfect items. A percentage of defective items can be reworked, and these products go through the rework process to become perfect and return to the consumption cycle. The goal is to determine economic production quantities to minimize the total cost of the system. The analytical solutions are each derived separately by Lagrangian relaxation method, and a numerical example is presented to illustrate and discuss the procedure. A sensitivity analysis is performed to investigate how the variation in the inputs of the models affects the total cost of the inventory system. Finally, some research directions for future works are discussed.

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One of the goals of the manufacturing industry in the globalisation era is to reduce defects. Due to a variety of factors, the products manufactured in the industry may not be defect-free. Six Sigma is one of the most effective methods for reducing defects. This paper focuses on implementing Six Sigma in the automobile industry's stator motor shaft assembly. The high decibel noise produced by the stator motor is regarded as a rejected piece. Six Sigma focuses on continuous improvement and aids in process optimization by identifying the source of the defect. In the Six Sigma process, the problem is measured and analysed using various tools and techniques. Before beginning this case study, its impact on the company in terms of internal and external customer cost savings is assessed. This case study was discovered to be in a high-impact area. The issue was discovered during the Core and Shaft pressing process. Further research leads to dimensional tolerance, which reduces the defect percentage from 16.5 percent to 0.5 percent.

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Overall Equipment Effectiveness (OEE) is a very powerful indicator for the performance evaluation of a manufacturing organization. However, determining the OEE target remains subjective and it’s usually based on the decision of concerned managers. In this paper, we tested the OEE target determination model based on the measured OEE. Such a method is based on the fuzzy logic principle and on two other decision-making support methods. To do this, we began with a literature review on OEE and its constituents. Then, a detailed description of the research methodology and the proposed model is provided. Thus, a case study in a manufacturing agri-food organization was conducted to test the proposed model and validate the obtained results.

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The aims of this research is to analyze effect to perceived organization support, symbolic incentives meaning, and knowledge sharing quality on innovative work behavior at e-commerce in Indonesia. The number of samples in this research that was examined were 160 samples of business owner or manager who seller their product in e-commerce, originating from the provinces of Special Region Yogyakarta, Central Java, East Java, and West Nusa Tenggara, Indonesia. We use purposive sampling technique for the data collection method. The result of this research indicate that perceived organization support has a significant positive effect on symbolic incentives meaning. Perceived organization support has a significant positive effect on knowledge sharing quality. Perceived organization support has a insignificant positive effect on innovative work behavior. Symbolic incentives meaning has a insignificant positive effect on innovative work behavior. Knowledge sharing quality has a insignificant positive effect on innovative work behavior.

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The Coronavirus (Covid-19) has become a threat to the world. The government has implemented various policies to prevent its spread, such as self-isolation, social distancing, etc. The regulation turned out to pose a big threat to many companies, especially in the retail sector. To survive in a pandemic, the company needs to ensure brand loyalty as an important factor in maintaining company stability. This study aims to determine the effect of Corporate Social Responsibility, Service Quality, Customer Satisfaction on Brand Loyalty, and the effect of Service Quality on Customer Satisfaction in coffee shop brands from the US. The method used is descriptive quantitative with 100 respondents from Greater Jakarta. The findings show that Corporate Social Responsibility and Service Quality do not directly influence Brand Loyalty, while Customer Satisfaction has a positive and significant relationship with Brand Loyalty. Meanwhile, Service Quality affects Customer Satisfaction positively and significantly.

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Previous studies have reported that trust is the main issue that needs to be resolving. (McKnight & Chervany, 2001). Trust proficiently leads people or organizations to acquire maximized benefits and potentially gives an organization a competitive advantage in markets, communities, and hierarchies (Robbins (2016), Semuel & Chandra (2014). The extent of this study revolves around develop consumer trust in the quality of cosmetic product scope.  Researchers have shown an increased interest in the cosmetics field as the average annual growth in the last twenty years is 4.5% and the rate of growth presume to continue over 3%.   The objectives of this research are to (1) understand factor involves in the process of build consumers’ confidence and trust virtually in offline and online business, (2) to determine the prominent information need to be an underline in marketing strategy, and (3) to understand how trust can affect consumer preference on cosmetics product. This study underlined cosmetic price, cosmetic brand name, and cosmetic country of origin are the prominent information that needs to underline in marketing strategy. Important issues were addressed and recommendations were made for prospect research.