“Going paperless” — eliminating hard copy documents in favor of digital storage—has been a goal of manufacturers for many years. For a quality group or lab, the benefits of going paperless are compelling, in regard to both environmental impact and data accessibility.
However, many manufacturers have not experienced the potential of a fully digital information workflow. In many of those cases “paperless” simply means storing documents as PDF files or as bitmap images, exchanging one static format for another. The data in these files is useful for archiving, but it is no longer an active part of the process.
Further down the paperless path
Supfina – a North Kingstown, R.I., developer and manufacturer of machine tools that produce fine and ultrafine surfaces in – has taken its own paperless workflow further. “We tend to be measurement intensive,” according to Supfina process engineering manager Joe O’Hearn. His team measures customer components at two critical points in the development cycle: during initial specification to verify their machines’ capability for an application, and again as part of the machine’s acceptance plan.
Supfina moved from paper to electronic storage in its measurement labs about 10 years ago. Printers were removed from labs; instead, inspectors measured parts and typed the results into spreadsheets that were saved to a server. If a part warranted further attention, its measurement data was saved as a PDF.
This was a step in the right direction but the process was time-consuming and the spreadsheet data still could not be re-analyzed as part of the process. “If any specifications or requirements changed,” O’Hearn recalled, “we’d need to go back into the lab again to run new measurements.”
The measurement software itself also presented a roadblock for a digital workflow. Most measurement systems are shipped with proprietary software that is optimized to acquire data on that instrument. The software’s analytical capabilities can be limited however, often outputting a short set of parameters and possibly a part profile.
Typically, the instrument software can analyze only data that has been measured with that particular instrument. “Our users often have very sophisticated roughness callouts,” he explained. “Those requirements may involve specifications for both roughness and waviness, with varying evaluation lengths. To do that with the software that came with the instruments would be very tedious.”
Stored data is critical
Supfina made big step forward came when the team began using “offline” surface-texture software to analyze data from their measurement instruments. Offline analysis software can be used away from the measurement system, freeing the systems for further measurements. Such software typically can import and analyze files from a range of instruments, rather than just one system. This allows Supfina to analyze and compare their results with data collected by their customers — an important part of the process development cycle.
Most important, data saved using offline software can be re-analyzed and re-used. When a new machine is being specified, for example, Supfina engineers can pull data from prior jobs and reanalyze it in the context of the new requirements, without remeasurement, which saves considerable time in the development cycle.
“The ability to re-analyze past data allows us to quickly help our customers understand the implications of new requirements on an existing process,” O’Hearn said. “The majority of our customers are manufacturing engineers responsible for multiple operations. They may not have the time or resources to analyze a new callout. We can go back to the baseline data from a machine runoff and tell them within a few minutes if the process will meet those specifications and, with a bit of further analysis, what kind of statistical capability they can expect.”
O’Hearn said that the ability to reanalyze data allows the company to quote new projects with a higher degree of confidence. “We can go back to earlier results of similar surfaces and see what was required to generate that surface. We have data from hundreds of jobs, but there is a handful of processes which I repeatedly go back to as benchmarks, to answer questions such as how many finishing steps will be needed or whether we meet capability on multiple surface roughness parameters simultaneously.
“The ability to answer those kinds of questions early in the quoting process substantially lowers the risk for us and the customer,” he noted.
Data analysis outside the lab
“Offline analysis software puts analysis capability in the hands of everyone working on a component,” according to Mark Malburg, president of Digital Metrology Solutions, which develops offline software for surface texture and surface shape. “It’s common in a manufacturing environment to take a part and a print to a measurement lab. The lab measures the part and returns a number which says whether the part and the process are in spec or not.
“There is a lot more to be learned from that data that could help uncover what has changed,” Malburg continued, “but when the analysis is simply printed or written down, we’re just left with a number, and we’ve lost the ability to study and re-interpret the data.”
Malburg said that keeping data in a format that can be re-analyzed allows it to be explored using varying conditions or different parameters. “We have seen great benefits at companies when engineers, technicians, and customers can interact with the surface texture. When they can work with the data at their desks, they can understand better how the texture impacts quality – and see what can be done to improve it.”
Offline analysis lets users outside of the lab study and compare data before and after processing to see the effectiveness of that process. O’Hearn described a typical example: the fine-finishing of a ground or hard-turned shaft. By showing the incoming shaft surface alongside the surface after finishing, Supfina can ensure that they have removed sufficient material to eliminate lead and other tool marks.
More efficient process control, improvement
The goal of developing a digital workflow is to increase efficiency throughout design, process development, and process improvement. “One question which comes up a lot is, ‘What has changed in the process?’” said O’Hearn. “The cell was making good parts last week, or better parts last year, and now a surface is out of specification. An example would be a surface not cleaning up after the superfinishing operation. If we can quickly compare an earlier part surface with a current surface, after each manufacturing operation, we can directly see what may have changed. Localized wear of the machine ways, say, may have introduced a waviness component that wasn’t there before.”
“We get vast quantities of data from manufacturing processes,” said O’Hearn, “but I find that the ability to compare two pictures of a surface, side-by-side, is often the best way to see what has changed. This is something you just can’t do when the analysis takes place entirely in the measurement lab. You have to have the data in your hands.”
“To understand a surface in the real world, you pick it up, roll it around, and explore it,” according to Malburg. “We need software tools that allow us to interact with surface data, rather than simply reacting to measured numbers. When we have both interaction and accurate numerical data, then we can really understand what is happening at the surface texture level, and we can efficiently act to improve a process.”
Supfina’s success is a testament to how a well-developed digital workflow can be achieved when measurement data can be re-analyzed for new projects, as a standard part of the process. Offline analysis allows for efficient, transparent data sharing that lets engineers, management and technicians share data across the process.
Mike Zecchino is the Manager, Technical Communications for Digital Metrology Solutions, a supplier of measurement software, custom metrology systems, metrology consulting for design and manufacturing issues, and measurement training for lab and shop-floor applications.