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by Steve Wise

It's complex. It's expensive. And you can't live without it: Airplanes wouldn't fly, bridges wouldn't stand and pharmaceuticals wouldn't heal. And, most likely, profits wouldn't be made. Statistical process control software is one of the most important investments you can make in your quality program.

It's also difficult to select. SPC software is used to analyze data and make intelligent decisions about products and processes. But, how do you make intelligent decisions about which SPC software package to buy?

Reviewing and selecting an SPC software product that's right for your organization requires time and money, certainly. However, the right choice can be made with confidence if you know what to look for before buying.

Not all SPC software competes for the same market. By knowing your needs from the start, you'll save a tremendous amount of research time. This article provides a list of topics that go beyond the obvious (i.e., SPC software that creates control charts, histograms, statistics and capability indices while supporting some form of data entry).

 

Post-analysis or real-time?

There are two categories of software that perform SPC functions: post-analysis and real-time. Terms such as high-end analysis, spreadsheets, data files and ODBC links describe post-analysis software. These applications either stand alone as spreadsheets or link to external databases like LIMS and ERP systems. Such solutions are popular in academic settings, laboratories and research environments.

Post-analysis statistical software is designed to "pull gold nuggets" from pre-existing data sets. With this software, data gets collected, and then someone else performs the analysis. Popular products that fall into this category include STATISTICA, MINITAB, STATGRAPHICS, SPSS, SAS, JMP, GenStat, Microsoft Excel and various Excel add-ins.

In contrast, real-time SPC products are accessible across corporate networks and specifically deployed on factory floors--where machine settings, product runs, measurement devices and people are always changing. In the real-time world, each new data point offers an opportunity to either make a process change or do nothing. Reliable real-time SPC software should provide effective alerts when process changes are necessary.

Because many organizations deal with these parameters, this article will focus on selecting a real-time SPC software product.

Flat files or database?

Data must be stored somewhere, either into data files or a database. Products that use data files typically maintain a separate file for each part. For example, 50 files are required to store data from 50 parts. If your company makes thousands of parts, you'll end up with thousands of data files. Setting up a single file is usually simple, but managing data files from thousands of parts can become overwhelming. However, organizations with limited SPC requirements get along quite well with a file-based system. If all you need are basic printouts of control charts and histograms, you might want to consider an Excel add-in, such as SPC XL. There's no point in spending thousands of dollars when an inexpensive solution will do the job.

In contrast, "databased" products are best suited in corporatewide SPC deployments where the same data must be accessed from multiple locations and workstations. Because all the data reside in a database, these products are excellent for comparative analysis across multiple parts, processes and test characteristics. Comparative analysis, however, requires a relational database organization. That is, all the raw data reside in one table, and the items tagged to the data--such as the part, process, test name, employee, specification limits and so forth--are referenced from other tables. A true relational database design employs "referential constraints" in which a database item, such as a part number, is defined only once in the database but can be referenced several times in the database. This type of design is very efficient and provides unlimited data analysis, sorting and comparison functionality. One warning, however: Simply because the data are stored to a relational database doesn't necessarily mean that the relational features of the database are used in the application. Finally, database tables should be accessible by third-party applications, such as Crystal Reports.

Compliance and validation

Obviously, the software you select must comply with any regulatory requirements under which your organization operates. The most common is the FDA's 21 CFR Part 11: Electronic Signatures and Records. This regulation is specific to the pharmaceutical and medical device community but will eventually become common practice across industries producing products that enter the human body. As a rule, applications that store quality records to data files can't become compliant. Any application that stores data to a local PC and then forwards the data to a master database is managing a system with two copies of the same quality record. This approach also violates 21 CFR Part 11.

When considering a specific SPC software product, ask for the validation document showing that the calculations are accurate. Also ask about the calculations' precision (i.e., How many significant digits are reliable?).

Shop-floor acceptance

If the software will be deployed on the factory floor, a representative from the floor must contribute to the decision process. The best way to test shop-floor acceptability is to pilot the software on the floor for a couple of weeks. This takes a lot of time and resources, so this step should only be done once you've narrowed down potential selections to no more than three products.

Features to look for include easy and intuitive navigation with very little button clicking. The interface should be clean and simple. Because the shop floor user may have limited computer and/or SPC knowledge, all unnecessary buttons and menus should be inaccessible unless the user has proper security privileges. Charts should be full-screen and/or locked in place, and individual windows shouldn't move or close. Big buttons, big message boxes and color designations that easily distinguish different screens and results are also important. The data collection interface must be simple and flow automatically through the collection steps in a logical manner.

Ensure technical support

Put the company's support service to the test. Call during your evaluation period and make sure that a representative can answer your questions. Ideally, the support person should be able to access your desktop using a safe collaboration Web tool such as WebEx. Ask to speak to the in-house statistician. He or she should be able to help you with recommended statistical tools for your needs. How the support service responds to these statistical requests will help determine the software's usefulness when an issue goes beyond simply making the software work.

Configurability and flexibility

Regardless of the software, setup involves at least two required phases: configuring a data collection plan and creating charts. Within the data collection plan, you specify the part, process, test characteristics, sample size, additional tag fields, data-entry method and collection sequence. Once this is set up and data have been collected, many software products don't allow any changes to the collection plan. But in reality, collection plans will probably need periodic modifications. For example, someone may want to add a test characteristic, change the sample size or change the collection sequence. To avoid future headaches, make sure all options are changeable on pre-existing data collection plans. Charts should be treated in the same way: They must be configurable and flexible.

Statistical correctness

For organizations that intend to make business decisions with their SPC data, two issues are very important. First, the control limits must be unique for a given part number, process and test characteristic. If the control limits' storage is based on a unique part and test characteristic (as found in most SPC products), the user must be careful not to mix processes within the same control limits. Tagging data with the process and then filtering all but one process isn't a good solution. Correct implementation with these products requires a different file or setup for every process that runs the same part. Software products that define control limits using unique part, process and test characteristic combinations are statistically correct and represent the most efficient control-limit management approach. Make sure the control limits are time-based (i.e., that updated control limits support effective dates). Control limits from old data aren't changed when updated limits are established on newer data.

The other issue involves standard deviation calculations. Specifically, the software must differentiate between the sample (long-term) and estimated (short-term) standard deviations. The long-term sigma (s, as calculated using the n-1 formula) uses all the data values, independent of subgrouping. Long-term sigma is used in Pp and Ppk calculations. Short-term sigma (^s) is calculated based on the range chart. Short-term sigma is used in Cp and Cpk calculations. Make sure these differences are understood and correctly applied within the software you choose.

Also make sure the software provider has industrial statisticians on staff. This will help ensure the software's statistical validity.

Integrating with other systems

The SPC package you choose should be able to integrate with other software products, such as those designed for document control and corrective action. Launching a rejection form when an event is triggered in the SPC program will prove very useful. For example, with such functionality, you're automatically able to tell an operator that the gage being used must be recalibrated in three days, or that the gage, based on the most recent gage R&R study, will consume 26 percent of the measured characteristic's tolerance. Some SPC products make such integration simple to implement. If you require integration, make sure you ask the SPC software provider how it can help you.

Value for money

Subtle differences exist among the various products, so as you close in on your ideal software, keep the following tips in mind to ensure you're getting your money's worth:

Don't pay more than 15 percent of the software's purchase price for the standard annual support fee. This should include unlimited telephone, fax, e-mail and Internet support, as well as all future updates.

Ask for copies of the company's software update logs. Look at the update record. Make sure the updates include substantial enhancements and new features, not just bug fixes.

Make sure that if the software supports e-mail, it isn't an imbedded proprietary e-mail system that requires a software license for anyone receiving the e-mail. The system should be SMTP-compliant, allowing e-mail to be sent across the Internet.

Look for a concurrent-use licensing scheme. The software can be installed on an unlimited number of workstations, but access to the software is controlled based on the number of purchased concurrent licenses.

Don't pay extra for Web publishing. Some companies have built-in utilities, at no additional cost, to allow automatic Web publishing of the SPC charts and data.

Beware of any company that wants to sell you its data collection and control charting software as well as a "high end" statistical product for the analysis. This not only increases the system's cost but also complicates deployment. Instead, make sure the software supports simple data extraction into any number of popular post-analysis statistical products.

Don't pay for validation documents.

Ask to use the software for at least 30 days at no cost. If you want to conduct a pilot test, expect to be given 90 days.

Don't pay for expensive software if Excel add-ins will satisfy your needs.

Ask around

There's no better way to candidly discuss potential software than to talk to companies that have already invested in it. Ask the software company for three types of references--and take the time to call them:

An organization that has made a recent purchase. Ask about its selection criteria, initial implementation issues and any buyer's remorse.

An organization that has been using the software for several years. Ask how the company has been treated after the sell. It should also have a wealth of knowledge in terms of lessons learned.

An organization in your industry. It will be able to speak your language. There are bound to be common problems that all organizations in your industry share; ask questions about how it has used the software to solve them.

Several providers offer excellent SPC software, so it's important to first determine your needs before you start shopping. This will help you limit your final selection to a couple of products. At this point, start a pilot program. Implement the product candidates in a limited fashion, and let all interested parties play with the software and express their opinions. Within a few weeks, the best choice for you should be obvious. By following these steps, you'll have the confidence that you're making the right decision.

About the author

Steve Wise, an industrial statistician and director of statistical methods at InfinityQS International, is a co-author of the original Boeing D1-9000 specification, Advanced Quality System for

Boeing Suppliers. He's also co-author of the book Innovative Control Charting, published by ASQ Quality Press. During the last 15 years, he's worked with companies implementing real-time, production-floor SPC and advanced quality management tools. Letters to the editor regarding this article can be sent to letters@qualitydigest.com.

For More Information

Click here to find Quality Digest's 2002 SPCSoftware Guide, a directory of more than 125 SPC software providers, complete with companies' contact information, Web site address and a brief description of their offerings.

Also visit Quality Digest's online SPC directory at www.qualitydigest.com/directories, where you can search vendors by region or by their products' specific functions (e.g., Pareto charts, simulation, regression and more).