Quality Engineering Tools Research Articles

QUALITY ENGINEERING TRANSFORMATION OVER THE YEARS AND ISSUES - A REVIEW

Traditional quality management and monitoring has been shown to be unsuccessful. Today, emerging companies are vying for more value to the consumer in order to ensure their maximum success and sustainability. Many businesses want to ensure that their goods and services are of high quality in order to attract customers. The current situation is implementing quality engineering solutions in industries. Quality engineering is the method of evaluating, handling, designing, and maintaining various systems in compliance with high standards. This method ensures that each stage of the product development cycle is subjected to a thorough inspection by quality engineers, reducing possible losses by eliminating defects from the start. Furthermore, highquality maintenance is important and should be made available for a long time after the product has been shipped. Customers' preferences are shifting significantly, necessitating improvements in design and production technology, which is becoming increasingly critical in satisfying individual customers. This necessitates paying particular attention to quality engineering. The paper starts with a review on quality emphasis over the last 37 years, quality concepts, and quality model evolution followed by i) a contrast of quality management and quality engineering, ii) developments in quality engineering tools and techniques, such as statistical process control (SPC), design of experiment (DoE), Taguchi processes, and quality function (QFD). This paper also looks at quality engineering-related problems. There are brief reviews of recent developments in well-known quality tools, such as statistical process control, quality function deployment, and design of experiment. The aim of this paper is to place quality engineering in context and emphasise its significance, as well as to present some issues at the frontiers of quality engineering.

Quality Engineering Tools Implementation a Comparison of Indian and Pakistani Business Organizations

Quality Engineering Tools Implementation a Comparison of Indian and Pakistani Business Organizations

Application of quality engineering techniques in the main domains of industrial engineering

Purpose: of this paper is to cover the main domains of industrial engineering based on the statistical and non-statistical techniques related to quality engineering. In this research, in addition to the review of the main domains of industrial engineering and the required specifications of technique, have been tried to present an integrated model of application of these techniques in order to create or increase the total score of productivity and sustainability in related scale with Analytic Hierarchy Process (AHP) approach. Design/methodology/approach: of this paper has been divided in two categories. The method of theoretical research consists of data collection tools, reference books, and several articles of the Iranian Center for Defences Standard. The method of practical research is the assessment of selected statistical and non-statistical techniques related to quality engineering, which have been deployed in the main domains of industrial engineering related to the manufacturing factories that are belonged to the selected industries of the Defence Industries Organization (DIO). Findings: of this paper consist of four main results. The maximum impact of standard statistical techniques in order to cover the main domains of industrial engineering and the required specifications of technique is related to the Statistical Process Control (SPC). Furthermore, the maximum impact of non-statistical techniques in order to cover them, is related to the Quality Function Deployment (QFD). The other results, which can be assessed with details, have shown that the maximum importance of the main domains of industrial engineering is related to the planning and manufacturing control and the maximum importance of the required specifications of technique is related to the mathematical analysis too. The total score of productivity and sustainability in related scale has been achieved to the upper than moderate level. In this research, the identification and determination of important factors, which have influenced on the productivity and sustainability have been done for the first time. The percentage of impact of the quality engineering techniques for both productivity and sustainability in the industrial engineering field is approximate to 70%. Research limitations/implications: of this paper suggest that the application of quality engineering tools including statistical and non-statistical techniques can be generalized to the other engineering or management fields with the same Analytic Hierarchy Process (AHP) or Analytic Network Process (ANP) approach in phase environments. Originality/value: of this paper have been extracted from the managers and experts involved with qualitative issues in the different levels of the Defence Industries Organization (DIO) and the Maham Group. This values are assessed from two aspects. Firstly, the validity of this research was carried out using expert’s opinions (Industrial advisers, Lead auditors of the Iranian center for Defences Standard and university professors). Secondly, all values of the research reliability are acceptable.

Statistical Process Control as a Failure Removal Improvement Tool

Abstract Continuous improvement should be a part of the strategy of every modern company that wishes to meet the requirements posed by the demanding, competitive market. The article presents a concept of applying a tool known from quality engineering, i.e. Shewhart control charts, for the improvement of the maintenance process in a small company providing services for the agricultural and construction industries. The improvement of the process included the reducing of the downtime of belt conveyors due to failures. Using control charts allowed the detection of interferences in the process and defining of their nature. Using other tools such as 5 WHY allowed the identification of the root causes of overly long downtimes and, consequently, formulation and implementation of improvements and preventive measures that were optimal for the organisation. The verification of actions taken has shown their positive impact on the process, which was reflected in the shortening of downtime and, subsequently, streamlining the failure removal process. The paper presents a possibility and validity of utilising quality engineering tools, such as Shewhart’s charts, 5 WHY or Ishikawa diagram, for improving the maintenance processes.

Improvement of Selected Logistics Processes Using Quality Engineering Tools

Abstract Increase in the number of orders, the increasing quality requirements and the speed of order preparation require implementation of new solutions and improvement of logistics processes. Any disruption that occurs during execution of an order often leads to customer dissatisfaction, as well as loss of his/her confidence. The article presents a case study of the use of quality engineering methods and tools to improve the e-commerce logistic process. This made it possible to identify and prioritize key issues, identify their causes, and formulate improvement and prevention measures.

Quality engineering tools in analysis of failure of longwall mining complex

Quality engineering tools in analysis of failure of longwall mining complex

SALES PERFORMANCE MANAGEMENT: A STRATEGIC INITIATIVE TO THE GROWTH OF MICRO AND SMALL BUSINESSES

Micro and small companies are lighting up in numbers and economic importance in the Brazilian market. In the sector of services, they already account for 27% of GDP. Given this importance, the purpose of this paper is to analyze how the integration of tools such as Planning Programming and Control of Production tools, together with the Quality Engineering tools such as performance management through indicators, can help to achieve the objectives of the organizations, especially small business, in the sales area. Boosting thus, strategically, these organizations to achieve and exceed their sales goals, become increasingly competitive, and growing in size and quality of service. The results obtained through the case study were satisfactory in 2014, where the signs of a crisis were already indicated in the country, this small business increased its sales by 12% compared to the year 2013.

Quality Insights: A pi tail mathematical postulation of the limit of quality

In the pursuit of better quality under the spirit of continuous improvement, it is appropriate to inquire about the potential limit of quality. Using quality engineering and technology tools and techniques, can we continue to improve quality indefinitely, inching toward the limit of quality ever so infinitesimally? This paper presents a postulation of an asymptomatic approach to the limit of quality based on the mathematical reasoning of pi. While there is no mathematical correlation of pi to the physical quality of a product, it is interesting and inspirational to conduct research on the move toward the best possible point on the quality curve. In this regard, the motivational question is 'what is the limit of quality?' The methodology of this paper suggests some interesting analogies.

The development of target-based posterior process capability indices and confidence intervals

One of the most popular quality engineering tools is the process capability index (PCI), which relates the allowable spread of a process defined by engineering specifications to the natural spread of a process. The traditional PCI does not account for the loss in quality when product characteristics fail to achieve their process target value. This research, in contrast, proposes indices, namely posterior PCIs, that consider the underlying result of observations after inspection. Utilising a truncated distribution as the basis for measurement along with a target-based quality loss function for capability analyses, several posterior indices are developed in this paper. A simulation technique is implemented to compare the proposed posterior PCIs with traditional measures. Finally, the confidence interval approximations for the posterior PCIs are derived. Our results suggest using the proposed posterior indices for capability analyses when industrial processes require that non-conforming products be scrapped prior to shipping to the customer.

The development of target-based posterior process capability indices and confidence intervals

One of the most popular quality engineering tools is the process capability index (PCI), which relates the allowable spread of a process defined by engineering specifications to the natural spread of a process. The traditional PCI does not account for the loss in quality when product characteristics fail to achieve their process target value. This research, in contrast, proposes indices, namely posterior PCIs, that consider the underlying result of observations after inspection. Utilising a truncated distribution as the basis for measurement along with a target-based quality loss function for capability analyses, several posterior indices are developed in this paper. A simulation technique is implemented to compare the proposed posterior PCIs with traditional measures. Finally, the confidence interval approximations for the posterior PCIs are derived. Our results suggest using the proposed posterior indices for capability analyses when industrial processes require that non-conforming products be scrapped prior to shipping to the customer.

Value Engineering-Based Method for Implementing the ISO14001 System in the Green Supply Chains

Numerous green regulations currently require companies to be responsible for their effect on the natural environment, in addition to achieving their economic goals. In view of this, many companies have implemented the ISO14001 system in their supply chain to comply with green regulations. However, implementing such a system involves technical and communication efforts; hence, an effective method is needed to support the implementation. In this paper, the authors propose a value engineering (VE)-based model with quality tools to support the implementation of the ISO14001 system in the Green Supply Chains. In it, they applied the framework of VE with the quality engineering tools Fishbone Analysis and Failure Mode Effect Analysis for the qualitative and quantitative analysis of green issues in supply chains to cover quality, risk, and value of the system. The proposed method was applied to a global electronics manufacturing company in Taiwan, and the application results showed positive outputs in terms of CO2 emission, power consumption, water consumption, and waste water recovery. Based on the evidence, academic and industrial implications are discussed.

Quality Engineering Tools Focused on Designing Remote Temperature Measurements for Inaccessible Locations by Using Light Components Parameterization of the Heated Materials

This paper is focused on research dedicated to measure the bucket wheel bearing temperature of the bucket wheel excavator (BWE). It proposes a measurement method for heating friction materials because is difficult to detect the temperature variation in the bearing. The major issue is to detect the generated infrared light according to the material detection. The temperature is considered the major signal of the wheel reliability and a remotely temperature detection method is proposed and because the sleeve bearing is a crucial part of the excavator a predictive measurements system for buckled wheel axis system was designed.

Matrix Approach to Analysis of Human Errors and their Prevention by Quality Engineering and Managerial Tools

We apply well-known quality engineering matrix techniques such as quality function deployment; Teoriya Resheniya Izobretatelskikh Zadatch (TRIZ); and failure mode, effects, and criticality analysis for characterizing, mapping, and preventing human error (or, at least, reducing damage caused by errors). Human errors (‘WHATs’, in the language of quality function deployment) are classified according to 10 characteristics, while 20 typical types (or protective layers)—‘HOWs’—in quality assurance systems are proposed for preventing/stopping/minimizing to some extent damage caused by the error. During the analysis of a specific system, any error is estimated according to its likelihood and severity, and every protective layer receives a score according to its effectiveness in preventing errors. Synergy or antagonism between protective layers may also be taken into account when calculating the effectiveness. The approach facilitates evaluation and comparison of the effectiveness of different quality assurance systems dealing with human errors. The authors emphasize the need to create a ‘recipe book’ based on a historical database, which will enable, after characterizing the potential human errors according to the 10 criteria mentioned earlier, application of the optimal prevention efforts. The proposed approach is illustrated by an example of product delivery errors analysis. Copyright © 2015 John Wiley & Sons, Ltd.

Metodología de Desarrollo de Software: MBM (Metodologia Basada en Modelos)

La ingeniería del software posee técnicas y herramientas que han maduradomucho actualmente se invierten grandes cantidades de recursos para potenciar la industria del software y convertirla en uno de los sectores estratégicos de crecimiento.Las empresas necesitan una estrategia sólida de Arquitectura Empresarial,se recomienda utilizar un software eficiente, motivo suficiente para que la Ingeniería de Software planteara metodologías para la elaboración de un producto de calidad. Hoy en día, aunque existen muchas de ellas con resultados muy buenos, no se cuenta con una estandarizada que al implementarla,permita desarrollar adecuadamente un proyecto de software que incluya la Gestión por Procesos de Negocio (BPM). Por eso se considera importante el diseño de una metodología práctica que contenga todos los procesos de creación de un producto de alta calidad, para utilizar en cualquier proyecto de software, encaminado a lograr la excelencia en la automatización de todos los procesos de negocio.

Inpatient Preanalytic Process Improvements

Phlebotomy services are a common target for preanalytic improvements. Many new, quality engineering tools have recently been applied in clinical laboratories. However, data on relatively few projects have been published. This example describes a complete application of current, quality engineering tools to improve preanalytic phlebotomy services. To decrease the response time in the preanalytic inpatient laboratory by 25%, to reduce the number of incident reports related to preanalytic phlebotomy, and to make systematic process changes that satisfied the stakeholders. The Department of Laboratory Medicine, General Services Section, at the University of Texas MD Anderson Cancer Center (Houston) is responsible for inpatient phlebotomy in a 24-hour operation, which serves 689 inpatient beds. The study director was project director of the Division of Pathology and Laboratory Medicine's Quality Improvement Section and was assisted by 2 quality technologists and an industrial engineer from MD Anderson Office of Performance Improvement. After implementing each solution, using well-recognized, quality tools and metrics, the response time for blood collection decreased by 23%, which was close to meeting the original responsiveness goal of 25%. The response time between collection and arrival in the laboratory decreased by 8%. Applicable laboratory-related incident reports were reduced by 43%. Comprehensive application of quality tools, such as statistical control charts, Pareto diagrams, value-stream maps, process failure modes and effects analyses, fishbone diagrams, solution prioritization matrices, and customer satisfaction surveys can significantly improve preset goals for inpatient phlebotomy.

Quality engineering tools used to design & optimize a mobile measurement station [Instrumentation Notes

During the design and construction of a distributed measurement system, design engineers face many basic questions. How does one properly choose a structure and actual solutions for the key elements of the system? Which elements are important? How does one guarantee a suitable level of operating quality and reliability? A broad knowledge base and technical experience are necessary to answer these questions. The consumer's expectations for the product need to be met. The designer's subjectivity should be minimized. In this column, we discuss the use of two tools, the Quality Function Deployment (QFD) method which comes from quality engineering rules and the Analytic Hierarchy Process (AHP) which comes from operations research. Implementing QFD during the design process can focus the attention of the designer on the most important elements of reliability and work quality. The AHP method helps the engineer make complex decisions in designing today's measurement systems that have many extreme optimization problems. Using these methods should decrease the cost of manufacturing and maintenance of measuring systems. We explain these methods and then show how they work in designing a distributed system for a mobile measurement station (MMS).

A Chemical Product Design Course with a Quality Focus

In recent years the chemical processes industry has faced important social, technical and economical challenges. As a result, the nature of its products, business strategies and ultimately the needs associated with the skills and technical knowledge of chemical engineers suffered enormous evolutions. One of such main changes is related to the emergence of chemical product design (CPD) as a specific and critical new field within the scope of chemical engineering. The importance of CPD teaching in chemical engineering courses is becoming well recognized by a number of different and leading universities. This paper presents a CPD course conceived and taught at the University of Coimbra to final year students in a fiveyear chemical engineering degree. It was developed with a special focus on the connections between CPD and quality engineering tools. The course was considered as a product by itself and conceived as such, namely through a clear identification of its strategic scope (mission, vision and values), aims (skills to be developed and knowledge to be acquired) and structural features (functional organization, time allocation, learning practices, programmatic contents and performance appraisal). A sample of two specific chemical product design projects carried out by teams of students is also described. This teaching experience has been very rewarding and stimulating from the perspectives of both faculty and students. It shows that CPD is indeed a new discipline that can and should be offered to more and more chemical engineering students all over the world, and that it can gain a lot through the application of quality management principles and quality engineering tools.