As many executives already recognise, knowing that production efficiency and capacity problems exist is one thing; however, effecting real and lasting change through a continuous improvement (CI) initiative is another, says Ian Huntly, CEO of Rifle-Shot Performance Holdings.
Often the challenge lies in determining the root cause and the full extent of operational problems, making it difficult to determine where and how to begin the CI programmeme.
But increasingly, manufacturers are discovering a surprisingly effective framework from which to tackle the CI challenge: the “six big losses”. Developed in the 1970s by the Japan Institute of Plant Maintenance (JIPM), this framework enables companies to examine their efficiency problem with an unprecedented level of granularity.
It also provides the necessary structure for tackling the problems, improving efficiency and capacity, reducing manufacturing costs and improving profitability.
When it comes to downtime, it is not enough to simply recognise that it is a problem. It is critical to also understand the causes for that loss. Furthermore, to drive change, it’s important to breakup downtime into its constituent parts. Besides reason codes, decision makers need to know if the downtime was caused by general wear and tear, operator error or maintenance technician delay, for instance.
They also need to know how long the downtime lasted and how long it took for the operator to respond, for maintenance personnel to identify the problem, and for the operator to get the line up and running again.
It is also important that the right people are empowered to make the data actionable. For instance the operator may be the person reporting the observed fault or symptom, but it’s the technician who can actually report the root cause. Both are needed to close the gap. And in most cases, the operator and the technicians are the only individuals who can provide the key information needed to address root causes.
Finally, the data collected must be 100% accurate and that’s where paper-based systems often fail. Trying to capture data manually requires someone to pick up a log at the end of the shift and report all the rate downtime they experienced during their shift. But in a fast-paced production environment, this is a futile task.
The chances of someone remembering every detail about the last eight hours are slim, which means that only a fraction of the data will ever be captured.
Setups and changeovers
An operator with no changeover target and no real-time visibility into how he or she is performing against that target, cannot be expected to work toward minimising changeover time. But in an environment in which equipment operators, supervisors and plant managers have full transparency into actual changeover times against targets, the dynamic is very different.
When provided with an allowance detailing how long each changeover should take, a video clip or diagram that explains how to complete the changeover, and an end-of-shift report that provides detailed feedback on actual changeover performance against the target, operators tend to change their behaviour.
Greater clarity into root causes can also lead to significant performance improvements. The ability to analyse changeovers by crew, shift or product and to easily determine when and where performance spikes are occurring allows managers to identify potential training issues.
Idling and minor stops
This category often represents a tremendous area for performance improvement. Idling and minor stoppages typically lead to other costly problems, in addition to lost time. In fact, even the smallest stoppage can kill the entire flow of a line in many production environments.
Fortunately, this is also one of the easiest areas to improve when the proper technology and feedback systems are in place. And in most cases, taking corrective action involves simple, painless changes in working practices rather than major capital investments.
But to achieve positive, sustainable improvements in this area, information must be captured on a minute by-minute basis. Moreover, it’s important to establish a process by which shop floor personnel can quickly and easily indicate the reasons for stoppages as they occur.
All too often operators have no way of communicating constant and repetitive line performance problems to senior management, so the problems continue unabated.
It is also critical that the feedback system be automated, not paper-based. Paper forms take too long to use in a fast-paced, real-time environment. They also lead to inaccuracies and discourage shop floor personnel from entering the information as it happens.
Reduced speed operation
Providing factory floor personnel with full, realtime visibility into line speed can have a dramatic effect on performance. Often referred to as the “Hawthorne effect”, a term used to describe behavioural changes when an individual knows his or her actions are being observed, improved performance is often immediate and significant.
Naturally, the objectives for most manufacturers include improvements in speed. But in addition, the objectives should include the ability to achieve an optimal balance between efficiency and product quality. In that case, the organisation’s performance management system should enable comparisons between production runs of the same product and by different operators.
This can help executives better understand what the line was actually running when the line speed decreased, so that a comparison can be made between variables such as operator, speed and product quality. A greater degree of granularity can also help identify equipment issues.
Scrap and rework (quality)
In terms of scrap and rework, knowing the size of the loss is not enough. To improve performance, manufacturers also need an accurate indication as to the source of the loss. Once again, because this information is difficult to capture manually as it happens, and because it often resides in a number of locations and systems, manufacturers lack the visibility necessary to make accurate changes.
What’s needed is a way to automatically capture the information and immediately feed it back to the individuals who can take action as soon as significant yield problems arise.
Also, to ensure that the minimum amount of product is scrapped, it is important to capture every single scrap instance as they occur and note how each of those correlates with other variables at the time of the loss – such as actual temperature, humidity and other key production factors that could conceivably impact quality.
Most manufacturers experience a certain level of product loss in virtually every start-up routine. However, if getting a line running at full running speed requires an operator to cycle the line two or three times, losing product in the process, there is generally an opportunity for improvement.
By having greater visibility into the effect of different variables on overall performance, managers can better determine the start-up conditions that are more conducive to waste, as well as the reasons for those conditions and how they can be addressed.
Moreover, embedding the standard operating procedure into the process can help operators determine exactly how the equipment should be set up, drastically minimising the amount of waste during start-up. Changeover alerts can also be helpful.
For instance, notifying the operator that he or she should be running the equipment at a certain rate or temperature can help minimise these unnecessary losses during a changeover.
For manufacturers, driving sustainable operational improvements is no longer an option it’s a requisite for survival. By employing the “Six Big Losses” framework to guide their continuous improvement journey, these companies can finally examine their efficiency problems with an unprecedented level of granularity.
When used in conjunction with practical, realtime performance management technology, this focused approach provides the necessary structure for tackling these problems, improving efficiency and capacity, reducing manufacturing costs and improving profitability.