During June of 1982 Tom Ridgeway retired from his duties as a U.S. Naval Aviator to perform engineering duties at a large non-destructive testing (NDT) company in Charleston, S.C. The lab specialized in the inspection of boilers that were utilized in the pulp and paper industry. As the director of the Engineering Department, Tom was assigned the task of developing a computerized reporting system that dealt with the reporting of ultrasonic thickness (UT) data that came from the boiler inspections. When the reporting system became a reality, a political problem arose within the company.

   The Problem: In order to view and analyze large amounts of UT data, Tom invented the “Coding” concept. This concept enabled a large amount of data to be placed on a single page and in proper relative position. The coding of data made the computer print look like a boiler wall. He also developed the “Coloring” concept that automatically drew attention to the problem areas of the boiler. Dark and red colors on the print represented problems areas in the boiler. These two concepts when used together was known as the “Imaging” of boiler data. The imaging of UT data opened up a whole new way of understanding the inspection. The intent of the report was to clearly display wear areas in the boiler so maintenance could be performed during the shutdown. However, while reviewing historical UT data via the imaging report, Tom noticed unexpected color patterns that did not follow known wear characteristics of boilers. At first he thought the data had been incorrectly entered into the computer. Investigation indicated the data had been entered correctly. Therefore, the software logic was reviewed to ensure the coloring of data was applied correctly. The logic was also correct. Still, the unexpected color patterns that showed large variances in the data were showing up throughout multiple boiler inspection reports.

   Determined to understand why the color patterns were appearing, Tom began investigating the NDT technician training. To his surprise, he discovered that most of the people conducting the inspections were not qualified technicians at all. A large percentage of the personnel on the job site were hired from the local labor pool and given a quick course on how to operate the UT instrument. Many of the newly trained technicians had never been in a boiler before and were operating by themselves. The company’s training officer explained that hiring people just prior to an inspection was in compliance with the American Society of Non-Destructive Testing (ASNT). The training officer based his opinion on the fact that a job foreman was somewhere on the job site. Meaning the newly hired personnel were not operating in the boiler by themselves. Tom was not comfortable with the answer supplied by the company’s training officer and decided to investigate the ASNT technician training procedures. He found that ASNT was not a regulating body and had no authority to mandate technician training. The training course offered by ASNT is named TC-1A and is only a recommendation, not a requirement to work in the NDT field. ASNT permitted the NDT labs to adopt and alter TC-1A for their own use. Therefore, even though ASNT did offer training, most technicians were trained by their employers. Many ASNT members were senior people in the NDT community such as lab owners and managers. The significance of this point is that the labs were using ASNT as a reference but were writing and administering their own courses. With the above point made, the training officer was correct in his explanation of how the company hired and used temporary people as technicians.

   Never-the-less, Tom was not comfortable with the idea that the newly hired personnel had so much freedom while inside the boiler performing the inspection. His opinion was based on the fact that so many large variances in the data were showing up by way of the imaging concept he had developed. Tom arranged a corporate level meeting to express his concerns. He opened the meeting by stating the imaging report was complete and that he had good news and bad news. The good news was that no other lab had the imaging type report thus putting the company in a good competitive position. The bad news was the mill engineer would rapidly notice the odd colored patterns in the report and ask why the UT data does not make sense. Because the report so easily revealed problems with UT data accuracy, the company decided to not use the reporting system as it was designed and asked Tom to get rid of the colors.

   The Solution: Tom could not comply with the mandate to get rid of the colors in the report and therefore resigned his position to start T.C. Ridgeway, Inc. (TCRI) during September 1984. The purpose of his company was to work directly for the mill and use the “Imaging” concept to qualify UT data while the boiler was still down for inspection. Not being an NDT lab was TCRI’s most important feature. For the first several years, the NDT community lobbied hard against TCRI. The labs did not want a third party reviewing their UT data. Tom felt his third-party work was valid and would not back away from using the imaging report in behave of the mill engineer. It took several years to convince the NDT community that TCRI existed to help everyone involved with the boiler inspections.

   Since 1984 TCRI has gained acceptance, thus the opportunity to study the paper industry and the NDT community by speaking with many mill engineers, lab owners and individual technicians. The problem of consistently acquiring accurate UT data is a problem that all labs struggle with. The explanation is not simple as to why the data is not as accurate as industrial America thinks it is. No lab intends to do a poor job in the field. However, not many labs have the luxury of being 100% prepared for the inspection. Even though the lab’s invoice to the mill is quite high, the business environment the labs operate in does not yield much of a profit margin. The competitive bidding process causes one lab to cut corners, thus the others must follow in order to get the purchase order from the mill. Because the UT inspection does not produce anything other than numbers, it is difficult for the mill engineer to determine if the lab did a good job. Many times the mill’s evaluation of the lab is dependant upon whether or not the data was obtained and the scaffolding came out of the boiler on time. If the scaffolding came out on schedule, the lab must have done a good job. The mill making such an assumption creates a false sense of security.

   Another point worth mentioning is the attrition rate of personnel in the NDT community. Because of the harsh life the technicians endure on a daily bases, they often find employment elsewhere. No matter what industry, a high turn-over rate has a negative impact on the quality of goods or services a company produces. The NDT community is no different and has an annual attrition rate of about fifty percent (50%). Even with such a high attrition rate, some people never leave the NDT community. These people are honest, hard working individuals that have dedicated their lives to doing a good job. These people are usually the managers that direct the activities of all the new technicians on the job site.

   Unless the mill engineer has a third party reviewing the UT data during the shutdown, he must depend on the lab to pass judgment with respect to data quality. When all of the technician training issues, the competitive bidding issues and attrition rate issues are all factored in, it would be wiser for the mill engineer to seek advice from a third party whose only job is to evaluate data quality. Therefore, TCRI was not designed to be a lab and will give the mill an unbiased evaluation of the data. Keep in mind that in 1984, Tom’s employer chose not to use the Imaging report because it was to revealing. Since 1984 many labs have written imaging and trending software to report their boiler inspection data. Most of the time the software was used as a marketing device but was rarely used to actually trend all of the data from any given boiler. If you were a lab manager, would you use your own software to reveal that the data often gets thicker with time? Probably not. Only the trend plots that show the data getting thinner with time would be delivered to the mill engineer. The trend plots that show the data getting thicker with time would simply be absent. This is a very significant point. The inherent UT inaccuracies that cause a trend plot to show growing tubes are the same inaccuracies that cause trend plots to show wearing tubes. If only those plots that show tube wear are delivered to the mill, the engineer would think the boiler is wearing out faster than it actually is. The above mentioned point is causing industrial America to replace boiler tubes years before the tubes need to be replaced.

  While at the job site, TCRI’s mission is to review the data gathered by the lab that is working for the mill. With this in mind, the TCRI software was designed with checks-and-balances that quickly scrutinize the data. One such routine produces a list of UT inspection locations whose values differ significantly from the values obtained from the same locations during the last inspection. With authority from the mill, TCRI issues this “Verification list” to the lab so a second set of data can be obtained. Another checks-and-balances routine is named “Police”. For any given inspection, the routine compares every elevation of UT data to every other elevation of data, to determine if there are any matching data files. By definition, a matching set of data files means the data from one location in the boiler, exactly matches the data from another location in the boiler, point for point. The mathematical probability of a match actually occurring is very, very low. Never-the-less, TCRI finds matching data files several time a year from various labs throughout the country. This does not mean the labs are unethical. However, it does mean that some individual in the lab decided to manufacture some of the data in the computer instead of gathering it from the boiler.

   To make this document fair and balanced, it must be mentioned that sometimes the mill is its own worst enemy. If the request for quote (RFQ) prepared by the mill engineer is not specific, the labs do not know how to bid or what equipment and personnel to bring to the job site. The old saying, “the inspection this year is just like last year, except for ...” leaves a lot of room for confusion. The RFQ needs to have things like the schedule, the scope-of-work, the material specifications and individual responsibilities all well defined. There is nothing wrong with competitive bidding. It just needs to be administered on an even playing field. When everyone knows what his job is and when it is supposed to be complete, the probability of acquiring better UT data goes up.

   Today, the TCRI Technical Database System (TDS) is the result of twenty years of blood sweat and tears. Participating in hundreds of boiler inspections and collecting feedback from dozens of NDT labs and mill engineers has made the TDS what it is today. The software does a superb job of helping the mill engineer understand his UT data and does far more than what can be presented on this web page. The software is designed to be installed at the mill where it would be used as a technical tool and record keeping facility. The UT analysis routines are for budget and maintenance planning. The power generation industry requested it, therefore TCRI built it! Let us help you manage your boiler inspection data. It is the only thing we do and we are very good at it.