Specifically targeted at the food industry, this state-of-the-art text/reference combines all the principal methods of statistical quality and process control into a single, up-to-date volume. In an easily understood and highly readable style, the author clearly explains underlying concepts and uses real world examples to illustrate statistical techniques. This Third Edition maintains the strengths of the first and second editions while adding new information on Total Quality Management, Computer Integrated Management, ISO 9001-2002, and The Malcolm Baldrige Quality Award. There are updates on FDA Regulations and Net Weight control limits, as well as additional HACCP applications. A new chapter has been added to explain concepts and implementation of the six-sigma quality control system.
Considering the ability of food processing companies to consistently manu facture safe foods with uniform quality over the past 20 or 30 years without these new tools and new systems, one might expect that quality control improvements would be marginal. On the other hand, these changes have already provided sub stantial opportunities for process and product improvement. This second edition is intended to update the basic concepts and discuss some of the new ones. Preface to the First Edition If an automobile tire leaks or an electric light switch fails, if we are short-changed at a department store or erroneously billed for phone calls not made, if a plane de parture is delayed due to a mechanical failure-these are rather ordinary annoy ances which we have come to accept as normal occurrences. Contrast this with failure of a food product. If foreign matter is found in a food, if a product is discolored or crushed, if illness or discomfort occurs when a food product is eaten-the consumer reacts with anger, fear, and sometimes mass hys teria. The offending product is often returned to the seller, or a disgruntled letter is written to the manufacturer. In an extreme case, an expensive law suit may be filed against the company. The reaction is almost as severe if the failure is a dif ficult-to-open package or a leaking container. There is no tolerance for failure of food products.
If an automobile tire leaks or an electric light switch fails, if we are short changed at a department store or erroneously billed for phone calls not made, if a plane departure is delayed due to a mechanical failure - these are rather ordinary annoyances which we have come to accept as normal occur rences. Contrast this with failure of a food product. If foreign matter is found in a food, if a product is discolored or crushed, if illness or discomfort occurs when a food product is eaten-the consumer reacts with anger, fear, and sometimes mass hysteria. The offending product is often returned to the seller, or a disgruntled letter is written to the manufacturer. In an extreme case, an expensive law suit may be filed against the company. The reaction is almost as severe if the failure is a difficult-to-open package or a leaking container. There is no tolerance for failure of food products. Dozens of books on quality written for hardware or service industries discuss failure rates, product reliability, serviceability, maintainability, warran ty, and repair. Manufacturers in the food industry cannot use these measure ments: food reliability must be 100%, failure rate 0%. Serviceability, main tainability, warranty, and repair are meaningless terms to food processors.
A comprehensive treatment for implementing Statistical Process Control (SPC) in the food industry This book provides managers, engineers, and practitioners with an overview of necessary and relevant tools of Statistical Process Control, a roadmap for their implementation, the importance of engagement and teamwork, SPC leadership, success factors of the readiness and implementation, and some of the key lessons learned from a number of food companies. Illustrated with numerous examples from global real-world case studies, this book demonstrates the power of various SPC tools in a comprehensive manner. The final part of the book highlights the critical challenges encountered while implementing SPC in the food industry globally. Statistical Process Control for the Food Industry: A Guide for Practitioners and Managers explores the opportunities to deliver customized SPC training programs for local food companies. It offers insightful chapter covering everything from the philosophy and fundamentals of quality control in the food industry all the way up to case studies of SPC application in the food industry on both the quality and safety aspect, making it an excellent "cookbook" for the managers in the food industry to assess and initiating the SPC application in their respective companies. Covers concise and clear guidelines for the application of SPC tools in any food companies' environment Provides appropriate guidelines showing the organizational readiness level before the food companies adopt SPC Explicitly comments on success factors, motivations, and challenges in the food industry Addresses quality and safety issues in the food industry Presents numerous, global, real-world case studies of SPC in the food industry Statistical Process Control for the Food Industry: A Guide for Practitioners and Managers can be used to train upper middle and senior managers in improving food quality and reducing food waste using SPC as one of the core techniques. It's also an excellent book for graduate students of food engineering, food quality management and/or food technology, and process management.
The organization of quality control. Health problems in food. Chemical aspects. Food processing and nutritional values. Microbiological quality control. Statistical methods in quality control. Tasting panels. national and international standards. Quality standards and specification in the food industry.
Revised and expanded, this Second Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments.
Food quality systems; control charts; fundamentals; sampling; test methods; product specifications; process capability; process control; sensory control; net content control; design of experiments; vendor quality assurance; implementing a quality control program; the computer and process control.
"Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines.Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences.A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, provides students with a solid base of conceptual and practical knowledge."--
Producing products of reliable quality is vitally important to the food and beverage industry. In particular, companies often fail to ensure that the sensory quality of their products remains consistent, leading to the sale of goods which fail to meet the desired specifications or are rejected by the consumer. This book is a practical guide for all those tasked with using sensory analysis for quality control (QC) of food and beverages. Chapters in part one cover the key aspects to consider when designing a sensory QC program. The second part of the book focuses on methods for sensory QC and statistical data analysis. Establishing product sensory specifications and combining instrumental and sensory methods are also covered. The final part of the book reviews the use of sensory QC programs in the food and beverage industry. Chapters on sensory QC for taint prevention and the application of sensory techniques for shelf-life assessment are followed by contributions reviewing sensory QC programs for different products, including ready meals, wine and fish. A chapter on sensory QC of products such as textiles, cosmetics and cars completes the volume. Sensory analysis for food and beverage quality control is an essential reference for anyone setting up or operating a sensory QC program, or researching sensory QC. - Highlights key aspects to consider when designing a quality control program including sensory targets and proficiency testing - Examines methods for sensory quality control and statistical data analysis - Reviews the use of sensory quality control programs in the food and beverage industry featuring ready meals, wine and fish
STATISTICAL QUALITY CONTROL Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectors This book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept. Statistical Quality Control: Using MINITAB, R, JMP and Python begins with a brief discussion of the different types of data encountered in various fields of statistical applications and introduces graphical and numerical tools needed to conduct preliminary analysis of the data. It then discusses the basic concept of statistical quality control (SQC) and Six Sigma Methodology and examines the different types of sampling methods encountered when sampling schemes are used to study certain populations. The book also covers Phase 1 Control Charts for variables and attributes; Phase II Control Charts to detect small shifts; the various types of Process Capability Indices (CPI); certain aspects of Measurement System Analysis (MSA); various aspects of PRE-control; and more. This helpful guide also Focuses on the learning and understanding of statistical quality control for second and third year undergraduates and practitioners in the field Discusses aspects of Six Sigma Methodology Teaches readers to use MINITAB, R, JMP and Python to create and analyze charts Requires no previous knowledge of statistical theory Is supplemented by an instructor-only book companion site featuring data sets and a solutions manual to all problems, as well as a student book companion site that includes data sets and a solutions manual to all odd-numbered problems Statistical Quality Control: Using MINITAB, R, JMP and Python is an excellent book for students studying engineering, statistics, management studies, and other related fields and who are interested in learning various techniques of statistical quality control. It also serves as a desk reference for practitioners who work to improve quality in various sectors, such as manufacturing, service, transportation, medical, oil, and financial institutions. It‘s also useful for those who use Six Sigma techniques to improve the quality of products in such areas.
