Statistical Process Control 101

Learn all about SPC for manufacturing.

Overcoming Obstacles to Effective SPC

Statistical process control can help manufacturers achieve continuous process improvement—when it is implemented properly. Watch out for the following obstacles, which can sideline your SPC efforts. 

SPC Obstacle #1: “We’re Too Unique for SPC”

If management (or others within the company) believe that company circumstances are so unique that statistical process control cannot be applied to processes, they are likely to argue that even considering SPC would be a waste of time. This obstacle tends to crop up for manufacturers that experience the following:
 
  • Short runs (i.e., frequent process or product changes)
  • Lack of metrics
  • Fear of change
  • Proprietary or unique processes

To overcome this obstacle: Explain that if a process creates output, then SPC can be applied. The first step is to start collecting data to show how the process behaves. After metrics are defined and data are collected and plotted, it is easy to see that the process does have measurable characteristics. Educating employees in short-run process control methods is a great way to show them that they are not alone. While one likes to feel special, the truth is that most companies that feel too special for statistical process control are the ones that can benefit the most from using SPC. 
 

SPC Obstacle #2: “SPC Will Fix Everything!”

SPC isn’t a cure-all. If no action is taken pursuant to the knowledge gained from SPC analysis, then implementing SPC software for manufacturing or setting up dozens of control charts is not going to improve anything. A control chart can’t eliminate variation and won’t solve all your quality problems.

SPC is the foundation of an effective process-improvement methodology, but there are numerous other tools that should be used. Management teams that expect to solve all their quality problems simply by implementing SPC but doing nothing with the data typically abandon the initiative when it doesn’t miraculously solve every problem.

To overcome this obstacle: SPC education must include an understanding of what SPC does. SPC brings to light common cause and special cause variations, but other tools are needed to reduce or eliminate variation. Train employees to use other process-improvement tools to help reduce variation and create a Corrective Action or Process Improvement team to work on projects.
 

SPC Obstacle #3: Misunderstanding Limits

Before SPC implementation, many manufacturers collect product data and compare them to specification limits. If the product is within the boundaries set by the customer, the manufacturer assumes that the process is performing fine…in-control. This use of data and limits is called product control, not process control.

When SPC is implemented, you use control limits that are based on process behavior to truly control the process. However, some companies keep specification limits on their control charts, base control limits on something other than true process variation, or set control limits to a standard other than +3 sigma. If control limits do not accurately represent the process, they are useless and can cause more harm than good.

To overcome this obstacle: Ensure that employees understand that control limits are the voice of the process and show how the process is performing, whereas specification limits are the voice of the customer and are independent of process stability. Specification limits do not belong on a control chart. Control charts always use control limits, which are set at 3 sigma units on either side of the central line and are based on data. Drill into all employees that control limits are never based on any calculation using the specification limits. 
 

SPC Obstacle #4: Too Much Tampering

When a process is in state of statistical control, with primarily common cause variation present, any adjustment to the process is tampering and will only increase the variation. Operators often adjust machines that don’t need adjustment; good operators have a natural tendency to tinker with a process to try and make it perform at its best. Management can aggravate tampering by insisting that operators adjust a process when process data aren’t where management wants them.

These impulsive reactions create uncontrollable gyrations in the process. When the process deteriorates, management tends to blame the operator, resulting in distrust and damaged morale that can ruin an SPC initiative—and do irreversible harm to employee/management relations.

To overcome this obstacle: All employees, especially management, must be trained to understand variation and the dangers of tampering. Each data point on a control chart is independent of the previous one. Processes must be allowed to operate in their natural state if you are to understand the common cause variation. There is a saying in the SPC community, “Don’t do something, just stand there.” Training must include how tampering creates bias and nullifies control charts. 
 

SPC Obstacle #5: Lack of Management Support

Employees who are expected to implement SPC without adequate training and resources will undoubtedly cause the initiative to fail. In many cases, management attempts to save money by scrimping on training, but the money saved will be outweighed by the wasted cost of an unsuccessful SPC program.

In some cases, employees get adequate training, but supervisors and management do not—and so do not support the initiative. If management is uncomfortable with SPC concepts, they will either avoid necessary actions (because they are uneasy with the changes) or recommend process changes based on a misunderstanding of process control. Either way, the SPC initiative suffers.

To overcome this obstacle: Management must provide the necessary resources to conduct thorough training for every employee and every level of the organization—including all levels of management. This training must be repeated at regular intervals, as new employees must be trained, and experienced employees need refresher courses.

Management must be involved with the SPC initiative so that employees know that management believes in and understands SPC. Management must set realistic goals for process improvement and base their analysis on solid metrics. Executive management should also involve front-line management in the selection of the areas to which to apply SPC. Doing so will increase the likelihood that front-line management will take ownership of the system and help it to gain acceptance with employees.

All managers must understand how decision-making should change after SPC is implemented. Remember Shewhart’s Fourth Foundation of Control Charts: Control charts are effective only to the extent that the organization can use, in an effective manner, the knowledge gained. Management must empower employees to make decisions gained from SPC analysis. 
 

SPC Obstacle #6: Lack of Data Integrity

Data that lacks integrity has a devastating effect on analysis and decision-making. Using “bad” data can be worse than having no data. Data can be biased in many ways: Operators might be “rounding off” values before recording data. Subgrouping might not be rational. A measuring instrument might not be suited for the task or might be damaged or out of calibration. 

To overcome this obstacle: Before the SPC initiative, set rules for data collection and analysis. Criteria should include the least number of significant digits for the measurement system, how much error (including gauge Repeatability and Reproducibility, bias, and linearity studies) is acceptable, calibration frequency for measurement instruments, rules for determination of outliers, and which actions to take with outliers. Sampling practices must be evaluated to prove rationality, and the sampling frequency must be sufficient to detect shifts in the process.

 

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