One of the most common statistical quality control measures used in this industry is the Control Chart. These charts plot the variation in price as a function of process capability, and help managers make informed decisions about which processes need to control and which can be left uncontested. Control charts based on statistical variation are extremely useful because they allow managers to evaluate process capability against observed variation in price over time. In doing so, they can decide whether or not to change any processes that may be deemed to be insufficiently productive.
There are several different types of statistical process control charts. In the UK, most process improvement companies use one or more of these forms. Some examples include the Performance Management Chart, the Material Quality Chart and the Processes Improvement Chart. These quality control charts provide key performance indicators for managers to use to evaluate their own organization and to determine whether any changes to processes should be made.
Another tool in the quality control process is the Quality Index, which compares the performance of an organization against various aspects of a variety of statistical variables. These can include production process variation, working and efficiency standards, and environmental performance. The index can determine whether or not an organization meets its goals, which is the very objective of quality management.
Another way to track production process capability is through the Variance Index, which compares the variations across time. It can determine whether or not the organization is on the right track. It compares historical variation with statistical variation. As part of the process, organizations also develop a list of project problems that must be solved and a list of potential Solutions for these problems. These project problems are called challenges, while potential Solutions are termed opportunities.
While analyzing a company‘s production, it is crucial to identify both opportunities and threats as well as the status of a particular process or activity. A quality dashboard can help by showing both the issues and potentials, while allowing easy analysis by a user. This is especially true in the case of complex projects where there may be multiple solutions for a single problem. By analyzing the status of a specific process, the manager can evaluate it in relation to its current use, and what impact it could have on the organizational growth.
For statistical quality control, a company must first determine what kind of metrics will be most useful to the organization. In doing so, they must set some standards, which will determine what kind of information to collect from its processes. In addition, it must establish what standard of accuracy would constitute a successful statistical quality control program. This will ensure that a company will know what kinds of statistical measures it should be collecting, how these data are supposed to be collected, and whether or not these measurements are adequate to achieve the statistical quality control goals.
These factors must be evaluated during the planning stage of a project. The results of these evaluations must then be incorporated into the quality plan. For example, if a company plans to measure product quality based on the cost savings that it is expected to realize over a period of time, this will translate to a statistical quality control program that focuses on this criterion. On the other hand, if the company is to concentrate on the satisfaction of its customers by way of a superior product or service, then this will be reflected in the business plan and the operational strategies that go along with it.