Engineering Statistics for Manufacturing Systems
Engineers not only provide the science behind the design of the products of today's technological revolution, they also help ensure that the production of those products -- and virtually any mass manufactured product -- remains within specification. To do these things, engineers use the tools and techniques of applied statistics. Through the application of various statistical tools and techniques, engineers can evaluate, improve, and optimize the processes and products of manufacturing systems. Statistics is used in the control of the various manufacturing processes and in quality control. In addition, engineering statistics is used in the design and analysis of experiments that are used to characterized, improve, qualify, and optimize the manufacturing processes as well as product performance and reliability. Through the use of statistics, engineers help keep processes in control and contribute to the effectiveness and efficiency of the organization.
Engineers are essential for the success of any large-scale manufacturing operation. Not only do engineers provide the science behind the design of the products of today's technological revolution, they also help ensure that the production of those products remains within specification. However, it is not only the production of high technology products that require engineering expertise. The large-scale production of any product, including clothing, paper products, and canned goods, requires the expertise of an engineer to help make sure that the product is being produced within the specifications for which it was designed. This is important not only because the consumer expects a certain level of quality and consistency in a product (for example, one would not purchase a can of peas in which the lid was not tightly sealed), but also because the rejection of products that are outside of specifications or manufacturing processes that result in excess waste cost the organization money.
Uses of Applied Statistics in Engineering
Applied statistics is one of the disciplines that engineers use in their tasks at manufacturing facilities. Through the application of various statistical tools and techniques, engineers can evaluate, improve, and optimize the processes and products of manufacturing plants. Engineering statistics are used in several areas of manufacturing systems.
First, statistics are used in the control of the various manufacturing processes and in quality control. This discipline comprises a set of procedures or processes that help ensure that products or services comply with predefined quality criteria or otherwise meet the requirements of the client or customer. Quality control activities include:
- The collection and statistical analysis of data to determine whether the process includes systematic (i.e., nonrandom) variation in quality.
- Monitoring and inspecting products or services vis à vis predefined specifications or quality standards.
- Determining the cause of variation.
- Developing and implementing changes to help meet target quality goals.
The tools and techniques of statistical process and quality control have numerous benefits. In particular, they help engineers monitor manufacturing processes to determine when a problem has occurred so that the process can be brought back under control. When a process is stable and assignable causes of variation have been eliminated, these tools and techniques can help engineers analyze manufacturing processes and compare their output with specified tolerances.
In addition, engineering statistics are used in the design and analysis of engineering experiments that are used to characterize, improve, qualify, and optimize the manufacturing processes as well as product performance and reliability. The proper design of experiments and application of the appropriate statistical technique allows engineers to draw valid conclusions from the quality and other data collected. Engineers also use statistics techniques in the development of mathematical models that represent the system or situation being studied so that impact of various variables on the end result can be better understood. The use of statistical tools in the analysis of data from experimental studies assists engineers in better understanding the data that are gathered from various manufacturing processes. Statistically analyzed experimental designs have a wide range of applications to manufacturing processes. An understanding of what statistics can and cannot do helps engineers to better design experiments that will yield the answers to questions about manufacturing processes. Specifically, this understanding can help in the development of better hypotheses that can be realistically tested using real world data. In addition, this understanding can help engineers interpret the results of experiments and to apply them to the real world in order to continuously improve manufacturing processes.
Solving Engineering Problems
The successful solution of engineering problems such as the improvement of manufacturing processes must be based on an understanding of variability and how to apply the principles of mathematical statistics to real world problems. Mathematical statistics is a branch of mathematics that deals with the analysis and interpretation of data. Mathematical statistics provides the theoretical underpinnings for various applied statistical disciplines, including engineering statistics, in which data are analyzed to find answers to quantifiable questions. Engineering statistics is the application of these tools and techniques to the analysis of real world problems for the purpose of business decision making. Specifically, the discipline of engineering statistics is concerned with the collection, presentation, analysis, and use of data in order to solve real world problems and make practical decisions. Statistical methods are useful in helping engineers understand the underlying variability that can be observed in systems and phenomena as are frequently observed in manufacturing processes. For example, in manufacturing, some proportion of products always has defects no matter how standardized or efficient the process. Statistics can help engineers better understand why this occurs and design processes or equipment that will help reduce the number of defective products produced.
Statistical process control is the application of statistical techniques to measure and analyze the variations that occur in any production process and to monitor the consistency with which the processes used in manufacturing result in products that are within their design specifications. Statistical quality control is the use of statistical techniques to measure and improve the quality the processes. These processes have nothing to do with the quality of the product itself: it only monitors whether or not that product is within specification. Statistical process and quality control are not tools for improving the quality of the design, but only help monitor whether or not a product is being manufactured as designed.
Errors in Manufacturing Processes
Modern manufacturing and automation technology go a long way toward...
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