Senior Tech Editor Rich Merritt reports on how industrial OEMs are marshalling the forces of smart sensors and diagnostics software to make sure trouble doesn't ride roughshod over machine utilization.
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Excerpt from the June 2006 article
MAXIMUM machine uptime is the ultimate objective of modern manufacturing. That's why we cover topics such as simplified mechanicals, standardized controls, vibration analysis, and remote diagnostics. These are thoroughbred technology applications that industrial machine builders everywhere rely on to help improve their machines.
Diagnostic sensors and predictive software are a growing part of these approaches to increasing uptime. After all, it's far better to fix problems when they're small and easily serviced than it is to fix a machine in the field after it begins acting up or breaks, and then holds up a customer's production line.
In fact, the field evidence of this strategy is finally out there. We found machine builders using built-in diagnostics, and also discovered that the necessary hardware and software is getting downright cheap. You may soon realize that you can't afford not to build diagnostics into your machines.
Hey, Machine: Phone Home
Many diagnostic systems allow machine builders to communicate via the Internet to machines located anywhere. However, allowing technicians to analyze a situation and help a customer troubleshoot problems is only half the solution. The other side is enabling the machine to phone home, and send regular reports and diagnostic data for further analysis.
There's no reason why advanced analyses can't be done in a central location, where the cost of analysis software can be spread over the installed base of machines. A cheap data-gathering device in the machine could send data via phone lines, the Internet, or a cell-phone connection to the central office. Emerson's system allows remote devices to communicate to the central processor via phone lines. They could be calling a processor in your home office just as easily. The LabView system can have executables installed in machines at no extra licensing cost.
Consequently, you probably could set up an independent, remote, data-gathering system in your machine for about $500, including hardware and HMI/SCADA software. The system wouldn't interfere with your normal machine controls. It would "mine" whatever condition monitoring data was needed from the PLC, MCC, network and I/O, package it up, and ship it all back to your home office once or twice per day. If it detected an alarm condition, it could notify the local operator and the home office.
Sounds far fetched? Hardly. Collecting condition data remotely and processing it in a central location is being done every day by machine builders and other OEMs. For example, InfinityQS International, a vendor of SPC software in Chantilly, Va., reports that its clients include Ball Corp., a manufacturer of packaging machines; Raytheon, a maker of silicon wafers; FMC, a manufacturer of food processing equipment; and Phoenix Automation, an on-line inspection company for the automotive industries. All of these connect multiple machines—sometimes hundreds in a single plant—to servers that perform statistical analyses on parts, production, and machine performance.
Steve Wise, director of statistical methods at InfinityQS, says the data-gathering requirement at each machine is minimal. "There needs to be some form of software that will write the desired information to a flat ASCII file," he explains. "Our software can be set up to automatically strip data from that file on a regular basis. Alternatively, an HMI software developer can write data directly to our ActiveX subgroup component."
Also, HMI/SCADA vendor Wonderware has a software suite with asset management, machine monitoring, and statistical analysis programs. Nancy Venable, product manager, explains that machines can be connected to the software suite in several ways. "All the machines in a customer's plant could be connected to one server through a local plant network, or the machine builder might opt to embed a small standalone single-node solution for monitoring and control," she explains. "A hybrid solution contains both elements, where the standalone nodes are embedded into the machines, and a central server collects information from the nodes for processing."
What Do You Do With All That Data?
Let's assume you've installed condition monitoring sensors and small data gathering devices on your machines in the field, so that now you have hundreds of machines sending in buckets of data to your central server every day. Each machine phones in every day, and sends you a flat file or a SQL-compatible file containing a few thousand bytes of vibration spectral data, ambient temperatures, motor rpm, on/off cycles, pressures, flow, etc. Now what do you do with it?
Each machine's normal operating conditions can be analyzed by SPC or similar software to look for trends. Jeff Cawley, engineer at Northwest Analytical, an SPC vendor, says SPC can detect problems before they become problems. "SPC is applicable to monitoring any parameter, such as measuring shaft load and bearing wear," he explains. "SPC differentiates signals from noise, is more sensitive to equipment and process deterioration than simple inspection systems, and enables a dynamic, intelligent system response."
Consequently, specific problems can be solved, such as a suspected vibration. The more advanced software at the central server can fully analyze spectral data coming from the remote machine and render a diagnosis. Your service engineers can also access a machine's complete history, and run specific analyses to help troubleshoot a user's machine.
Problems in multiple machines also can be analyzed. For example, let's say that motors are failing on a regular basis, but only in certain machines. An SPC analysis can find the problem, adds Steve Wise, director of statistical methods at InfinityQS. "The analysis is trivial," he claims. "The challenge is gathering the right kind of data from the field. If each failure is recorded, the system, using Pareto charts and simple run charts, is able to establish a personality for each machine. To see if any one machine was acting differently than similar machines, we can add multiple machines to the study, and organize the graphical representation to display machine-to-machine differences. Meaningful correlation studies require tracking specific suspect parameters with specific failure modes."
Wonderware's product manager, Nancy Venable, adds it's possible to define a variety of downtime conditions based on triggers coming from one or more machine inputs. "As machines operate, all this information is collected and stored," she says. "In time, trends from the database appear that determine the leading causes of downtime, when they occurred, why they occurred, what shifts have the highest downtimes, which machines have the lowest downtimes, and why. This information can then be used to determine patterns of failure and appropriate preventive maintenance procedures."