Quality Engineering最新文献

{"title":"Problem framing: Essential to successful statistical engineering applications","authors":"R. Hoerl, D. Kuonen, T. Redman","doi":"10.1080/08982112.2022.2113098","DOIUrl":"https://doi.org/10.1080/08982112.2022.2113098","url":null,"abstract":"Abstract The first two phases of the statistical engineering process are to identify the problem, and to properly structure it. These steps relate to work that is often referred to elsewhere as framing of the problem. While these are obviously critical steps, we have found that problem-solving teams often “underwhelm” these phases, perhaps being over-anxious to get to the analytics. This approach typically leads to projects that are “dead on arrival” because different parties have different understandings of what problem they are actually trying to solve. In this expository article, we point out evidence for a consistent and perplexing lack of emphasis on these first two phases in practice, review some highlights of previous research on the problem, offer tangible advice for teams on how to properly frame problems to maximize the probability for success, and share some real examples of framing challenging problems.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"34 1","pages":"473 - 481"},"PeriodicalIF":2.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43460027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical engineering – Part 2: Future","authors":"C. Anderson‐Cook, Lu Lu, William Brenneman, J. De Mast, F. Faltin, Laura Freeman, W. Guthrie, R. Hoerl, Willis A. Jensen, Allison Jones-Farmer, Dennis Leber, Angela Patterson, M. Perry, S. Steiner, Nathaniel T. Stevens","doi":"10.1080/08982112.2022.2106440","DOIUrl":"https://doi.org/10.1080/08982112.2022.2106440","url":null,"abstract":"Abstract In the second of two panel discussion articles focused on the evolution of statistical engineering (SE) as introduced by Roger Hoerl and Ronald Snee, a group of leading applied statisticians from academia, industry, and government present their perspectives on what the future might hold for this important movement. The invited panelists discuss the challenges and opportunities presented by the emergence of data science and the abundance of large amounts of data. They also consider the possible paths forward for SE, and the roles for statisticians in academia, industry, and government. The final question addresses what additional skills would be helpful to increase the effectiveness of the practice and advance SE. As with the first article, the format of the article follows the order of a posed question, a summary of key ideas, and then the detailed individual panelist answers. The article seeks to inspire statisticians to consider their possible role to leverage the potential of SE to solve important problems.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"34 1","pages":"446 - 467"},"PeriodicalIF":2.0,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45172325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response surfaces, blocking, and split plots: A predictive distribution case study","authors":"John J. Peterson","doi":"10.1080/08982112.2022.2102427","DOIUrl":"https://doi.org/10.1080/08982112.2022.2102427","url":null,"abstract":"Abstract This article presents a case study re-analysis of a complex response-factor data set involving a split-plot design with blocking for two quality responses. The analysis presented herein makes use of multivariate predictive distributions to both optimize and quantify the risk of meeting specifications. This article shows how a modern approach using predictive distributions can provide deeper insight and improved process optimization over the use of classical response surface methodology tools such as “overlapping means” plots and (mean-based) desirability functions. It is shown how the R and the Stan programming languages are used to facilitate the analysis.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"35 1","pages":"172 - 191"},"PeriodicalIF":2.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46634707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical engineering – Part 1: Past and present","authors":"C. Anderson‐Cook, Lu Lu, William Brenneman, J. De Mast, F. Faltin, Laura Freeman, W. Guthrie, R. Hoerl, Willis A. Jensen, Allison Jones-Farmer, Dennis Leber, Angela Patterson, M. Perry, S. Steiner, Nathaniel T. Stevens","doi":"10.1080/08982112.2022.2106439","DOIUrl":"https://doi.org/10.1080/08982112.2022.2106439","url":null,"abstract":"Abstract After more than a decade since the introduction of Statistical Engineering by Roger Hoerl and Ronald Snee, a group of leading applied statisticians from academia, industry, and government were invited to discuss their perspectives on progress made, the current status of this important movement, and what future Statistical Engineering holds on the path forward in a series of two panel discussion papers. In this first article, the invited panelists focus their discussion on the past and present of Statistical Engineering. They discuss notable advances and current obstacles to progress. They also consider the unique value added by Statistical Engineering, and the possible addition of decision making to the body of knowledge. The format of the article consists of the posed questions from the moderators, a summary of key ideas from all the panelists, and then the individual detailed answers. The goal of this series of articles is to inspire statisticians to consider their possible role to advance the adoption of Statistical Engineering to solve important problems.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"34 1","pages":"426 - 445"},"PeriodicalIF":2.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45425943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of manufacturing process in low variety high volume industry with the coupling of cloud model theory and TOPSIS approach","authors":"Faaiz Ahsan, Afshan Naseem, Y. Ahmad, Zunaira Sajjad","doi":"10.1080/08982112.2022.2107934","DOIUrl":"https://doi.org/10.1080/08982112.2022.2107934","url":null,"abstract":"Abstract Failure Mode and Effect Analysis (FMEA) is one of the most commonly used techniques for identifying and minimizing potential failures in various products and process designs. The traditional FMEA approach has limitations due to generic rating scales and experts' number-based assessments, which might not produce the desired results. The current research uses a hybrid approach of coupling Cloud Model Theory (CMT) with hierarchical Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to deal with uncertainty, including randomness and fuzziness in the identification of risks and failures in a cigarette manufacturing industry. The results show that this hybrid approach is more effective in classifying failures in the production process. The findings reveal that out of the three fundamental units of cigarette manufacturing machinery, most of the failures affecting the production of the cigarette manufacturing process belong to MAX, which supports filtration and inspection of filtered cigarettes. The study identifies salient problem areas that the managers must give special attention to enhance the production process's efficiency. The significance of the study lies in the identification of failure modes with rank order which the managers will find quite valuable for finally achieving the desired level of customer satisfaction and production efficiency.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"35 1","pages":"222 - 237"},"PeriodicalIF":2.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43892066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improvement projects with an environmental focus: A novel approach for prioritization","authors":"Ambika M. Raja, R. Raju, R. Raju, Sanjeev S. Raja","doi":"10.1080/08982112.2022.2105149","DOIUrl":"https://doi.org/10.1080/08982112.2022.2105149","url":null,"abstract":"Abstract Employment of a systematic approach for prioritization of improvement projects and addressing the voice of the stakeholders are imperative for organizations in the current business circumstances. This study suggests a novel approach that employs multi-criteria decision-making (MCDM) methods for project prioritization. A combination of step-wise weight assessment ratio analysis (SWARA) method and house of quality (HOQ) is used in the calculation of the importance of criteria, followed by utilization of criteria importance in COmplex PRoportional ASsessment of alternatives with grey relations (COPRAS-G) for selection of the final project. It considers environmental effects alongside traditional criteria. Innovation in this study is in the combination of the MCDMs with HOQ and prioritizing projects considering the impact on the environment. The advantages are efficiency and simplicity. The practical focus of the approach is illustrated using a case example. The approach is used for the prioritization of projects that apply the Define–Measure–Analyze–Improve–Control (DMAIC) framework in a Six Sigma organization. The evaluation of three DMAIC projects suggested taking up Project C. The illustration has shown applicability in real-life situations. Thus, the novel approach identifies an environment-friendly project that satisfies the stakeholders the most. The utilization of Grey MCDM method makes the approach suitable for use in an uncertain environment.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"35 1","pages":"1 - 14"},"PeriodicalIF":2.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59458693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding interactions between mixture components and process variables","authors":"R. Snee, R. Hoerl","doi":"10.1080/08982112.2022.2083516","DOIUrl":"https://doi.org/10.1080/08982112.2022.2083516","url":null,"abstract":"Abstract The study of mixture component effects in the presence of process variables has been of interest since the work of Scheffé. A key advantage of designed experiments in general is the ability to estimate and interpret interactions. A unique feature of mixture-process experiments is the potential presence of interactions between the mixture components and the process variables. The classic approach to interpret these has been to use contour plots and evaluate individual interaction coefficients in Scheffé mixture-process models. It is proposed to study the interactions along the Cox component axes, which greatly enhances the insight into the nature of these interactions that can be obtained from contour plots. Further, we propose an alternative analysis that produces estimates of the process variable main effects in mixture-process models. Both graphical and analytical methods are presented. This approach provides an overall view of the main effects and interactions that is consistent with how these terms are evaluated in factorial and response surface experiments with only process variables. Limitations of the classic approach are identified and discussed. Three examples are included to illustrate the approach.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"35 1","pages":"1 - 19"},"PeriodicalIF":2.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44248119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An improved FMEA model considering information quality in a multi-granularity probability linguistic environment","authors":"Linhan Ouyang, Yanhong Nie","doi":"10.1080/08982112.2022.2106438","DOIUrl":"https://doi.org/10.1080/08982112.2022.2106438","url":null,"abstract":"Abstract As a significant analytical tool in reliability management, FMEA has been extensively used in various fields. Nevertheless, conventional FMEA has been criticized for some defects. To compensate this situation, this article proposes an improved FMEA method under the environment of probabilistic linguistic terms. The multiformity and indeterminacy of experts’ assessment information is depicted by applying probabilistic linguistic term sets, and then evaluation information is fused based on information quality and Dempster-Shafer evidence theory. The different action priority is adopted to determine the sequence of failure modes. Finally, a case study is presented to verify the applicability of the proposed method.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"35 1","pages":"207 - 221"},"PeriodicalIF":2.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43831801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A conversation with William Q. Meeker","authors":"N. Doganaksoy","doi":"10.1080/08982112.2022.2107935","DOIUrl":"https://doi.org/10.1080/08982112.2022.2107935","url":null,"abstract":"Bill Meeker is a Professor of Statistics and Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He has done research and consulted extensively on problems in reliability data analysis, warranty prediction, reliability test planning, accelerated testing, risk assessment, nondestructive evaluation, and statistical computing. He is the coauthor of the first and second editions of Statistical Intervals and Statistical Methods for Reliability Data, both published by Wiley and Achieving Product Reliability, published by Taylor and Francis. He has won numerous awards for his research and publications. He is a fellow of the American Society for Quality, American Statistical Association, and American Association for the Advancement of Science. Necip: Please tell us about your childhood. Bill: I would like to start by thanking you and Quality Engineering for organizing this conversation. I am deeply honored. What I remember most about my childhood, say 1955 to 1962, is playing with my friends in the woods near our home. I recall being frustrated in the winter months because it would get dark shortly after we were out of school every day and there was little time to spend outdoors. We lived a couple of miles from the ocean on the north Jersey shore. In the summer months, I was allowed to walk with my younger sister and brother to the beach to play, as long as we did not go in the water by ourselves. My mother would finish her chores and errands and then bring us lunch and we would spend the afternoons swimming and enjoying the sun. Sometimes Mom would return home to make dinner and then Mom and Dad would return and we would enjoy dinner on the beach too. Once each summer (my father’s vacation time) our family would visit my great uncle’s cabin on a secluded lake in upstate Sussex County, NJ. We would have 10 or 12 days of hiking in the woods and swimming, boating, and fishing in the lake. It was a nice contrast from the crowded beach. My grandfather was a carpenter and my father had a good collection of hand tools that he used to build things and do repairs around the house. One weekend, when I was perhaps six years old, family members gathered to help clean out an old house in which my father’s recently deceased great aunt had lived for many years. To keep me busy and out of the way I was given an old radio from the house and some hand tools with the suggestion that I dismantle the radio. I think that I probably destroyed what today would be a valuable antique radio! Some years later during our municipality’s “junk weeks” (during which people could put out for pickup anything they wanted to throw out) I acquired old radios and learned that by swapping out bad tubes, I could get some of the radios working again. The others were dismantled for their parts from which I would attempt to build various gadgets. Thus, began my life-long interest in electronics which led me to ham radio—a hobby in which I am still involved when I have s","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"35 1","pages":"238 - 247"},"PeriodicalIF":2.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44319160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Power guidelines for process monitoring","authors":"Darwin J. Davis, James M. Lucas, E. Saniga, Michael S. Saccucci","doi":"10.1080/08982112.2022.2098763","DOIUrl":"https://doi.org/10.1080/08982112.2022.2098763","url":null,"abstract":"Abstract We present a process for designing monitoring procedures that includes practical power guidelines. These guidelines are based upon the average run length (ARL). The specific guideline metric is the ratio of the in-control ARL (ARLic) to the out-of-control ARL (ARLoc). Our recommended design process uses that ARL Ratio, in combination with the ARLic, ARLoc, and ARL curve, to design effective process monitoring procedures. For adequate power, we generally recommend an ARL Ratio of 20 or more and argue that monitoring procedures with ARL Ratios less than 10 should usually be avoided. An area of caution lies between ARL Ratios of 10 and 20, allowing us to propose a stoplight type model for use in monitoring procedure design. We also discuss exceptions to these guidelines as well as a methodology to incorporate power considerations in other approaches to control chart design.","PeriodicalId":20846,"journal":{"name":"Quality Engineering","volume":"03 1","pages":"130 - 141"},"PeriodicalIF":2.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41250038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}