How close to 100% reliable is your most critical equipment… the equipment that should perform as intended the first time, every time? It should be 100% reliable for safety, environmental or just plain business purposes. What organization would be satisfied with 45% reliability of these critical processes? Probably none. But under-performing processes are more common than many can imagine.
Reliability is NOT a maintenance program. In other words, maintenance alone can’t achieve the highest levels of equipment reliability in a sustainable manner. That’s because “maintenance actions” aren’t the solutions to most causes of unreliability.
Equipment reliability vs. process reliability
Reliability improvement is about driving out variations in the way equipment and processes perform. Improving equipment and process reliability is a constantly moving target, especially when more than one machine is involved; and when humans are involved; and when non-standard work processes are involved; and… well, you get the idea. Which now brings us to “process reliability.”
There’s often a tendency to focus on equipment reliability improvement. While that IS important, we must also consider the process within which the equipment operates.The “process” produces a useful output, while a piece of equipment may only contribute to a portion of that output. The causes of unreliability may be fairly easy to identify and correct when “equipment reliability” is the target. Conversely, when multiple equipment items must perform as part of a single process, the causes of process unreliability can be huge. Process reliability improvement will likely be a never-ending battle unless the causes of process unreliability are addressed in a balanced manner.
To fully appreciate Manufacturing Process Reliability Variables, take a look at the accompanying diagram of a filling-packaging process. Improvements to “process reliability” must focus on the entire filling-packaging line’s capacity to produce at desired levels of production efficiency, quality and cost per unit for each scheduled operating shift. To improve overall process reliability, we must understand what the process as a whole tells us about the causes of unreliability.
Expected vs. actual reliability
Again, to be reliable, the process“does what it is supposed to do in stated operating conditions for a stated period of time.” Every major part of the manufacturing process will affect the overall reliability. Start by counting the major UNITS contributing to manufacturing process variability. I count 89 major units associated with our diagram—including 18 humans conducting manual and equipment-related tasks (calculated 6 people X 3 crews).
Each of these 89 separate UNITS must function properly for the manufacturing process to produce a single product. But it’s about more than performing properly—they all must perform together, at the same time, in sequence. Every one of these 89 UNITS is a VARIABLE. Still, if it’s a reliable process it will do what it is supposed to do in stated operating conditions for a stated period of time: three eight-hour shifts per day/seven operating hours per shift.
Is 45% reliability acceptable?
For discussion’s sake, let’s say that to justify its existence, our hypothetical filling-packaging process is expected to perform at 85% reliability per shift. If we target each of the line’s 89 variables at 99% reliability, overall process reliability won’t exceed 40.9%. Ouch!
What if we narrow the field? Historical data indicates that nine of the line’s UNITS almost never have problems during scheduled operating times: electrical power systems (4), the compressed air system (1), the accumulators (2), bulk storage (1) and blend-mix (1). That means 89 variables are now reduced to 80. If we target each of them at 99% reliability, overall process reliability will be no better at (ouch, again) 44.8%.
And what about the operating crews? Two of our three crews are highly experienced and rarely (if ever) cause any problems. Unfortunately, that leaves us with a six-person crew that is quite inexperienced, still in training and routinely causing problems. Until this crew is fully qualified, it can’t be expected to perform all of its tasks at 99% reliability—which, alas, has a direct effect on overall process reliability. Don’t bother with the calculation here… but you get the idea. People MUST perform their tasks reliably, too.
So, is 44.8% reliability acceptable for the filing-packaging line? Is that what it was designed to do? Is that level of reliability going to meet the business goals? NO, NO and NO.
Improving process reliability
First, we must determine what the DATA is telling us about the major causes of unreliability. Is it a specific piece of equipment? A packaging component? Operator or maintainer errors? The key activity at this point is to determine the MAJOR causes—the most penalizing losses to the business (typically referred to as the “low-hanging fruit”).
The major causes of unreliability could lead to lower production rates than planned or higher defect rates than allowable, both of which translate into higher costs per unit and/or late deliveries to customers. Sometimes the cost of maintaining reliability can be so high that the cost per unit produced has a negative impact on the business.
The tools to address causes of unreliability will vary depending upon where they are focused. Take for example the following macro-level data analysis:
The takeaway from these documented causes of “cartoner jamming” is that not all are correctable by maintenance actions. In some cases, this may be related to improper tools used for adjustments or the fact that procedures are unavailable or not followed. Other deficiencies may include a lack of training to the level of being “qualified” to operate, set up or maintain; inadequate levels of detail in PM procedures; lack of timely PM completion; or no PM addressing the problem areas.
Critical factors in improving process reliability
You have a lot of pieces to put together in pursuit of 100% reliability. Keep all of them in mind.
Data collection, analysis and trending must be accurate (and reliable). Focus on the major causes, the most penalizing and chronic problems first. Think beyond “equipment reliability” and consider the process as a whole.
Finally, remember that the points of unreliability are a continually moving target. “Maintenance” is NOT the only solution for all causes of unreliability. Furthermore, creating a “reliability mindset” among the entire workgroup is essential. MT