Analyzer maintenance can incur unnecessary costs because, for simplification, it treats “identical” analyzer systems identically. For example, one process chromatograph may measure hydrogen in a clean gaseous stream and another apparently identical chromatograph may perform a similar measurement in a liquid stream laden with residual tars. Therefore, the analyzer system on the gaseous stream, under preventive maintenance, may incorrectly be assumed to have the same maintenance requirement as the analyzer system that can be contaminated by tars. This is an example of preventive maintenance that can result in reactive maintenance, when predictive maintenance would be superior because the latter anticipates actual failure.
Extending the example of the two chromatographs from the previous paragraph, predictive maintenance would distinguish the two analyzers with the chromatograph on the gaseous streams as requiring predictive maintenance perhaps monthly and the chromatograph on the tarry stream requiring similar service as frequently as weekly.
Continuing the example of preparing for lifetime preventive maintenance for a new chromatograph system, according to the Ramon Vorne article referenced in the sidebar, we must identify key performance indicators, or KPIs, that quantify waste, provide an early warning system for analyzer system failure, and provide information as to where improvements should be made. KPIs should be current or forward-looking metrics. The referenced article by Bob Vavra add that the key is to extract useful information from the KPIs to improve business and operating profitability.
Atkins and Rehaja suggest beginning the development of predictive maintenance procedures with a session including operations and analyzer maintenance personnel in a failure mode effects analysis (FMEA) to document what has gone wrong or can go wrong with the analyzer system. Paul Gruhn suggests that a similar team approach should be used for the Management of Change (MoC), which is usually required for analyzer projects. Most reliability texts provide guides and data sheets about FMEAs, or go to website www.isixsigma.com/tt/fmea/. The KPIs should emerge from the FMEA exercise. Table 2, taken from the Patton article, offers possible predictive maintenance information to include in a computerized maintenance database of equipment records. Table 3 offers possible KPI measures for the performance of “typical” gas chromatograph system. A more complete list of suggestions for the analyzer system database and KPIs can be derived from the lists of engineering and maintenance, plant, analyzer system vendor and safety lists in Battikha.
Gary D. Nichols, PE, is a principal control systems engineer at Jacobs Engineering Group. He can be reached at email@example.com.