"Since right-brain thinkers often gravitate to service jobs, the examples used in the book follow a theme that demonstrates the use of SPC in a service organization: an imaginary law firm. These examples can be adapted to any situation and they do not require knowledge of the legal profession. Also, the theme demonstrates the process involved in planning and deploying SPC, highlighting the human factors and workplace realities that are especially critical to putting SPC to work in a service environment."--BOOK JACKET.
Written in clear language, this hands-on manual simplifies the essentials for monitoring, analyzing, and improving quality. The authors explain how to set up and use variable and attribute control charts, as well as analyze frequency histograms, and evaluate machine and process capability.
Statistical Methods for SPC and TQM sets out to fill the gap for those in statistical process control (SPC) and total quality management (TQM) who need a practical guide to the logical basis of data presentation, control charting, and capability indices. Statistical theory is introduced in a practical context, usually by way of numerical examples. Several methods familiar to statisticians have been simplified to make them more accessible. Suitable tabulations of these functions are included; in several cases, effective and simple approximations are offered. Contents Data Collection and Graphical Summaries Numerical Data Summaries-Location and Dispersion Probability and Distribution Sampling, Estimation, and Confidence Sample Tests of Hypothesis; "Significance Tests" Control Charts for Process Management and Improvement Control Charts for Average and Variation Control Charts for "Single-Valued" Observations Control Charts for Attributes and Events Control Charts: Problems and Special Cases Cusum Methods Process Capability-Attributes, Events, and Normally Distributed Data Capability; Non-Normal Distributions Evaluating the Precision of a Measurement System (Gauge Capability) Getting More from Control Chart Data SPC in "Non-Product" Applications Appendices
Written by an experienced European Patent Attorney and scholar, this book sets out in detail the framework for protection of pharmaceutical innovation under the SPC Regulation. With a focus on both biotechnological innovation and secondary innovation, and through extensive reference to the case law, Ulla Klinge surveys the court’s evolving interpretation of legal and technical eligibility for this extended term of protection. This book provides clear and pragmatic tools to reflect and guide future practice, while offering key explanations and insights as to why and how technological developments challenge the legal SPC framework.
SPC for Right-Brain Thinkers is not simply another made-easy book on the subject of statistical process control (SPC). The guiding principle in writing this book was to make SPC accessible to that large group of individuals who would readily characterize themselves as right-brain thinkers. The challenge that right-brained thinkers face in understanding and applying SPC goes beyond the math; it is also a matter of approaching the subject from a different perspective altogether—--through the side door, if you will, where the inner workings of SPC may be seen in action. The book is also intended to serve the information needs of those who either own or work within the job processes wherein SPC is applied. Since right-brain thinkers are often inclined to gravitate to service-oriented jobs, the examples used in this book demonstrate the use of SPC in a service organization: a pseudo law firm called Advocate General. These examples demonstrate the basic principles of SPC in way that can be adapted to any situation. This is a book for those who: are inclined to label themselves as right-brain thinkers; are intimidated by math, possibly even the mere mention of something as ominous-sounding as statistical process control; and/or need only a basic understanding of SPC, perhaps from a systems perspective or as a potential user of an SPC tracking system.
There is no doubt that quality has become a major feature in the survival plan of organisations. With diminishing markets resulting from improved competitive performance and the associated factor of single-sourcing arrangements by the major organisations, it is clear that unless there is a commitment to change, organisations will lose their competitive edge. This will unfortunately mean elim ination and the resultant harsh realities that come with it for the employees. It has been said on many platforms that unemployment is not inevitable. Those organisations which recognise the requirements for survival know that quality, and its association with customer satisfaction, is now a key issue. Survival programmes based on quality improvement require an unrelenting com mitment to include everyone, from the Managing Director down, in an ongoing, never-ending involvement based on monitoring, and improving, all our activities. These Total Quality Management (TOM) programmes, whatever their specific nature, have a common theme of measuring and then improving. This text describes the philosophy and techniques of one type of involvement programme-Statistical Process Control (SPC). The material to follow suggests that SPC is a major element of any programme and, if properly applied, could be a complete programme in itself. Measuring and improving means that data must be collected, used, understood, interpreted and analysed, and thereby lies the difficulty.
On the manufacturing shop floor, the principle of "value comes from the production of parts rather than charts" crucially applies when using practical statistical process control (SPC). The production worker should need to enter only a sample’s measurements to get immediately actionable information as to whether corrective action (e.g., as defined by a control plan’s reaction plan) is necessary for an out-of-control situation, and should not have to perform any calculations, draw control charts, or use sophisticated statistical software. This book’s key benefit for readers consists of spreadsheet-deployable solutions with all the mathematical precision of a vernier along with the simplicity of a stone ax. Traditional SPC relies on the assumption that sufficient data are available with which to estimate the process parameters and set suitable control limits. Many practical applications involve, however, short production runs for which no process history is available. There are nonetheless tested and practical control methods such as PRE-Control and short-run SPC that use the product specifications to set appropriate limits. PRE-Control relies solely on the specification limits while short-run SPC starts with the assumption that the process is capable—that is, at least a 4-sigma process, and works from there to set control limits. Cumulative Sum (CUSUM) and exponentially weighted moving average (EWMA) charts also can be used for this purpose. Specialized charts can also track multiple part characteristics, and parts with different specifications, simultaneously. This is often useful, for example, where the same tool is engaged in mixed-model production. Readers will be able to deploy practical and simple control charts for production runs for which no prior history is available and control the processes until enough data accumulate to enable the traditional methods (assuming it ever does). They will be able to track multiple product features with different specifications and also control mixed-model applications in which a tool generates very short runs of parts with different specifications. The methods will not require software beyond readily available spreadsheets, nor will they require specialized tables that are not widely available. Process owners and quality engineers will be able to perform all supporting calculations in Microsoft Excel, and without the need for advanced software.
This publication contains the report of an expert meeting, held in Fiji in February 2004, organised to consider regional and national sea safety programmes, following on from a survey undertaken in 2003 in the Pacific Islands region. The survey highlighted the significant number of deaths in the region associated with small fishing boats which have received the least attention in terms of legislation, construction standards, enforcement strategies, regional discussions, training or proper use.
Do you feel you are drowning in a sea of data and wondering how you can learn from all of this information? While measuring quality efforts in healthcare is essential to the overall performance of any healthcare organization, it is also very complex, leaving many feeling overwhelmed and with a lot of unanswered questions: What are SPC methods and can they really help to improve healthcare? How can control charts be used to monitor key processes and outcomes? How can physicians use control charts to improve their clinical practice? In his latest book, Dr. Raymond Carey answers these questions and more as he helps to explain the need for, and the use of, SPC in healthcare. In Improving Healthcare with Control Charts: Basic and Advanced SPC Methods and Case Studies, Carey expands on his previous best-selling book, Measuring Quality Improvement in Healthcare, by providing more in-depth information on problems commonly experienced in constructing and analyzing control charts. He outlines specific SPC concepts, theories, and methods that will help improve measurement and therefore improve overall performance. Carey also presents many new case studies applying advanced methods and theory to real life healthcare situations.
