Manufacturing IT is sold on the promise of better efficiencies, improved productivity and more effective communication in teams. By using modern software, people working in the plants should be empowered with good information to make better decisions and achieve more. But is this always the case? Have we become too dependent on automation to the detriment of working smartly and more effectively? Are the software tools we use really adding value, or are they just another administrative burden?
Recently I needed to research FMEA as a technique to identify failure modes in a factory. FMEA is widely used in maintenance planning. It is can also be used in safety analysis and quality engineering. FMEA supports developing an effective maintenance plan by identifying critical equipment and ensuring that the risk of an unexpected breakdown is minimised. The results of an FMEA analysis can be a source of valuable information when incorporated into the planned maintenance system.
Once the FMEA information is uploaded, other day-to-day considerations come into play when prioritising work orders. For example, what is the manufacturers recommended overhaul procedure? What is the short term production requirement? Are we dealing with any crisis in the plant at the moment? When is the next planned shutdown? What is the cost of spares for critical equipment? Should we install a standby unit? Who is on leave today? And many more. A well-designed maintenance system should take all of this information, optimise around the constraints and produce feasible daily maintenance plans that consider all relevant factors.
So far, the theory sounds good. However, in reading more about this subject, I soon started coming across evidence that this approach has real challenges. This has been borne out by my own experience in a production plant. Despite maintenance costs being a substantial part of the operating budget and fairly decent software systems being on-hand, there is usually a high level of wasted effort in practice. Proper prioritisation of work is critical to ensure that limited resources remain focused on those activities that deliver the most value. Yet, despite good decision support tools, maintenance in many factories remains largely reactive and reliant on ad-hoc prioritisation techniques. For example, “each maintenance technician decides how to prioritise their own breakdown work orders”. Or, “people running the plant have a pretty good awareness of the equipment and they know better than any system what is critical and what is not”.
The reasons for the gap between FMEA theory and practice have been studied at length. My concern is the question – why are the IT systems and software not being used as intended? Surely software should bridge the gap between the complexity of the underlying analysis and provide simple, actionable steps to be taken? Why do people look for ways around the system? Are the tools fundamentally inadequate, too complex, or is there a computer literacy problem?
As we use more sophisticated automation technology, we need to get to grips with the fundamental questions above. It is no use implementing an advanced condition monitoring system with a shiny ‘digital twin’ capable of predicting breakdowns if the technician on the day’prioritises his own work orders’. Furthermore, unless the criticality of the piece of equipment is fully understood as part of the overall process, knowing that it is about to break down might be of little value because “the plant cannot and will not be shut down anytime soon, so we will just have to wait until it breaks”.
The designers of software tools that support manufacturing operations processes like maintenance, operations, safety, quality and so on need to reflect from time to time on how effective their systems are when used in practice. Over the past few years, far too many software systems I have seen have been nothing more than electronic forms to fill in with little else of value. A modest improvement on the old paper forms at best. In response to market pressures and client demands, software vendors also seem comfortable just bolting on more and more ‘features’, which contribute to bloat, eventually resulting in complex unfriendly applications largely decoupled from the reality on the ground. Unless the system truly helps a person in their job, it will be ignored and workarounds will predominate.
Elegant software design that is simple and meets a real need is not out of the question. Think about Apple and its ability to design mobile devices around ordinary users’ needs. An iPhone is a very sophisticated piece of technology, but most of this complexity is shielded from the user. There is no need for a user’s guide or training. It ‘just works’. The art of good software design is to hide away complexity from the user. To the end-user, the software tool must add value, make sense and must respect the individual’s own decision-making capability. Good software is designed with simplicity in mind from the ground up. Software should guide users and alert the user when things are not as expected. It should never replace sound judgement. The often-quoted French aviator and writer Antoine de Saint-Exupery once said, “Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away”. He would probably have made a great manufacturing systems designer.
About Gavin Halse
Gavin Halse is a chemical process engineer who has been involved in the manufacturing sector since mid-1980. He founded a software business in 1999 which grew to develop specialised applications for mining, energy and process manufacturing in several countries. Gavin is most interested in the effective use of IT in industrial environments and now consults part time to manufacturing and software companies around the effective use of IT to achieve business results.
For more information contact Gavin Halse, Absolute Perspectives,
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