Statistical Process Control

Introduction

Goetsch & Davis (2021, p. 306) define Statistical Process Control as follows:

Statistical process control (SPC) is a statistical method of separating variation resulting from special causes from variation resulting from natural causes in order to eliminate the special causes and to establish and maintain consistency in the process, enabling process improvement.

SPC is a methodology for maintaining and improving quality in production processes. It is implemented so as to control variation, eliminate waste, make processes predictable, perform product inspections, all with the goal of continual improvement.

In this post, the function of management in SPC is described. This includes management’s role in establishing quality measures and using control charts to maintain the level of quality. The actions management must take when quality from standards are also described.

Role of Management

Management’s primary responsibilities is to establish the production quality level so that it matches customers’ expectations. This requires setting measurable standards for product and service quality. By providing these standards, management demonstrates a commitment to quality, and to convert that commitment into a culture of quality. Research has shown that a gradual implementation of SPC is more successful than abrupt enforcement (Bushe, 1988), but SPC implantation does set the direction. These production quality levels are also required for control charts to be applicable to monitor and maintain quality (Rungtusanatham, 2001).

Management must also be involved in establishing budgets and to allocate resources in support of statistical process controls. This includes funding new machines and modern technologies that may be required for process improvements.

In addition, management is responsible for approving and sometimes conducting training programs needed by employees to use SPC effectively (Goetsch & Davis, p. 320).

Management is useful for evaluating and approving changes to processes suggested by other departments. In a sense, management is acting like a sieve, allowing only promising ideas through to line workers. Besides this, implementing these changes may involve new machinery or personnel changes, which are budgetary issues.

When Production Quality Slips

Management is also involved, or should be involved, in diagnosing problems when production quality falls below the established levels. In the context of manufacturing, machine operators would have the most direct understanding of the problem. It is managers’ responsibility to appraise the operator’s findings and approve the budget necessary to repair the machine or replace it.

Another situation that requires managerial intervention is when a supplier’s parts fall below the expected quality level. There are several courses of action, all of which require a manager’s decision.

One option is for the manager to contact the supplier to get an estimate for the time needed for them to resume manufacturing products that are within specifications. Based on this information, the manager may have to delay delivery to his customers or deliver less than what was promised.

A second option is to temporarily require the supplier to provide additional parts with the hope that there will be enough parts that are within specifications to satisfy customer orders.

A third option is to switch suppliers, which requires a manager’s decision. This will entail delays in fulfilling customer orders.

The least desirable option is to provide the customer with substandard parts. This is contrary to the philosophy of total quality management, however.

Conclusion

Statistical process control is a vital methodology for ensuring consistent quality and continuous improvement in production contexts. Management plays a pivotal role in successfully implementing SPC by setting quality standards, allocating financial resources for training, new machinery, etc. Managers are also essential for addressing deviations from quality standards. This could entail working with machine operators to diagnose and resolve such problems or making decisions about supplier relationships. By accepting these responsibilities, managers uphold the agreed-upon product quality standards as well as maintain customer satisfaction.

References

Bushe, G. (1988). Cultural contradictions of statistical process control in American manufacturing organizations. Journal of Management 14(1). https://doi.org/10.1177/014920638801400103

Goetsch, D. L. & Davis, S. B. (2021). Quality management for organizational excellence: Introduction to total quality (9^th ed.). Pearson.

Rungtusanatham, M. (2001). Beyond improved quality: the motivational effects of statistical process control. Journal of Operations Management 19(6). https://doi.org/10.1016/S0272-6963(01)00070-5