Statistical process control applies various statistical techniques to the measurement and analysis of 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. To control a process, one must understand how the control input affects that process. The first step in analyzing a process is to operationally define what that process is. Once the process is defined in detail, it can next be analyzed. This set of activities helps determine where in a process an error or failure is most likely to occur or where the process is most in need of reengineering. In addition, process analysis helps determine if there are any unnecessary, redundant, or irrelevant activities in the process that can be eliminated.
Keywords Business Process; Business Process Reengineering (BPR); Control Charts; Globalization; Mean; Quality Control; Sample; Standard Deviation; Statistics
Statistics: Process Analysis
The growing trend toward globalization in the twenty-first century brings with it both advantages and disadvantages. In many instances, globalization means that businesses have larger marketplaces in which to sell their products or services. However, the same global marketplace that offers increased opportunities to one company in an industry offers the same opportunities to the other companies within that industry. As a result, globalization also brings with it increased competition. To have a competitive advantage, therefore, companies need to offer their goods and services not only at a competitive price but also with a high level of quality if they hope to be competitive.
For manufactured products, the effects of globalization can be seen all around. The hookup instructions for the new television or stereo system come not only in English, but also Spanish, French, German, Korean, Japanese, or any number of other languages commonly spoken in the industrialized world. If we look at the box or the identification sticker on the machine, in many cases we will also find that the product was not even manufactured in the United States but halfway around the world. The semiconductor, automobile, and television production markets in particular have been deeply affected by foreign competition. In the mid-twentieth century, the phrase "made in Japan" signified a product of poor quality; in the twenty-first century, in many instances it has become a standard of excellence. It has been argued, in fact, that Japanese manufacturing techniques have surpassed those of the West and have cut deeply into the market share.
Statistical Process Control
Arguably, one of the primary reasons for this change is the increased emphasis on statistical process control. This approach to manufacturing processes emphasizes doing things right the first time rather than having to do things over to correct for faults in the first process. Statistical process control includes analysis of both short-and long-term capabilities, applying statistical methods to keep processes (and product quality) within tolerances, and continually analyzing and improving processes. Statistical process control applies various statistical techniques to the measurement and analysis of 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. These processes have nothing to do with the quality of the product itself: They only monitor whether or not that product is within specification. Statistical process and quality control are not tools for improving the quality of the design, but help monitor whether or not a product is being manufactured as designed.
Characteristics Common to Manufacturing Systems
Most basic manufacturing processes hold certain characteristics in common. As shown in Figure 1, these include a measurement of the state or condition of the process and a controller that calculates an action based on a comparison of this measured value with a set point (a predetermined or desired value). In addition, basic process control systems typically have an output signal that results from the calculation and that is used to manipulate the process through an actuator. The process itself reacts to this signal and changes its state or condition (e.g., correcting for errors or drifts in the process). Two of the most important signals used in process control are the process variable and a manipulated variable.• The process variable — or output of the process that is to be controlled — is automatically measured by a device in the field. The value of the process variable is used as an input for an automatic controller that takes action based on this value (i.e., either correct the process or let it continue as it is). • To control the process variable, the manipulated variable (also referred to as the control input) is adjusted. For example, if one needed to control the flow of a liquid into a tank, one would manipulate the position of the value (i.e., the manipulated variable) that controls the flow (i.e., the process variable).
Control InputTo control a process, one must understand how the control input affects that process. For example, if the input conditions are changed, it needs to be determined whether the output will rise or fall, the level of response that can be expected in the process, the length of time necessary to observe a change in the process based on the manipulation of the input, and what response curve or trajectory of the response is expected. Capability studies are used to determine the success or failure of a process and whether or not the use of statistical process control techniques or other action is appropriate. However, simply having a process under control is no longer sufficient in many situations for a company to maintain its competitive advantage. Modern organizations need to continually improve their business processes in order to stay ahead of the competition. Statistical quality control uses statistical techniques to measure and improve the quality of processes.
Analysis of Processes
The first step in analyzing a process is to operationally define what that process is. This activity is followed by process analysis, which is leveraged into an examination of ways to make improvements in the process. Defining the process involves observing the flow of manufacturing or service. The development of a process chart can be helpful in this activity, particularly when defining service processes whose flow may not be obvious at first glance.
- The first step in developing a process chart is to capture the total process from start to finish.
- Once this high-level description of the process has been captured, the next step is to fill in the details at the task or process operation level. This includes the specific actions taken at each stage in the process including any exceptions or subroutines.
- This definition is then further fleshed out to the procedure or process detail level that captures the individual steps within a task (e.g., individual hand movements). A sample total process chart is shown in Figure 2.
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