Dennis McCarthy of DAK Consulting discusses how advanced technology when used as part of a total productive maintenance programme can help to accelerate productivity gains and reduce downtime.
A common reason for the failure of advanced technology to deliver expected gains is too much focus on the technology itself and not enough on how it will be used.
For example, technology to support condition monitoring is often presented by providers as a way to reduce downtime. The reality is that gains are only achieved when the digital alarm is underpinned with actions to respond to it.
In addition, more alarms are not necessarily a good thing because a large number of poorly organised alerts can overwhelm human sensory and information processing capacity. A countermeasure to this ‘siren call’ of technology is to link advanced technology selection to the steps of a total productive maintenance (TPM) road map.
Although often presented as purely operator maintenance, TPM was developed to deliver “continuous improvement in effectiveness through cross-functional teamwork”. At the heart of TPM is a process to engage production, maintenance and relevant support functions in working through a structured road map to firstly stabilise effectiveness (zero breakdowns), then optimise asset performance.
Underpinning the road map process is research which highlights that only around 25% of downtime is due to poor inspection routines. Roughly double that amount of stoppage time comes as a result of accelerated wear due to contamination or lack of lubrication, or human error resulting from weak work routines, skill and knowledge gaps.
Without improvement to these two areas first, advanced condition monitoring is unlikely to deliver lasting gains.
Taming technology
A TPM road map developed by DAK Consulting based on work with manufacturing and process industry organisations is available to view at www.dakacademy.live/asy
The first phase involves actions to establish basic condition standards, reduce equipment wear rates and prevent the causes of human error. In addition to reducing breakdowns, this also improves collaboration between production and maintenance, encouraging new thinking and innovation.
An advanced technology tool that supports this first road map phase is the digital twin improvement glide path. This is used to compare actual performance against improvement glide path targets which have been set to track the gains from actions taken to improve basic conditions, work routines / compliance and contamination control.
The improved quality of feedback from digital notifications can then be combined with the use of data modelling and machine learning analysis tools to support the development of understanding about how to achieve asset stability. That includes:
• Clarifying the notifications that indicate ‘normal’ conditions and the response needed to deal with abnormal conditions;
• Providing recommendations for planned maintenance windows;
• Providing suggestions for refining process parameters to deal with factors such as variation in material quality or environmental conditions.
Digital notifications can also be used to coordinate:
• Work instruction review cycles;
• Change request progress;
• Work completions;
• Learning and compliance steps.
At this stage, one of the real gains from combining the TPM road map with advanced technology tools is the clarity it provides regarding the impact of maintenance best practice on asset effectiveness, operational flexibility and total manufacturing costs.
Ratcheting up performance
During the next phase of the road map, the digital twin glide path is used to define and optimise process capabilities to remove the causes of unplanned interventions.
This phase is characterised by actions to understand and eliminate the causes of minor quality defects. In addition to the increased time between intervention, the outcomes include fewer defects, improved material yields, lower energy use and a greater understanding of the mechanisms that impact on process control.
The gains from the TPM optimisation phase extended the mean time between intervention for one manufacturer such that the company was able to run additional night shifts during peak demand months without additional labour.
That lowered inventories, increased material yields, improved flexibility to demand fluctuations and reduced development time for new products.
The application of advanced technology as part of a TPM programme could accelerate progress towards achieving such gains from the three to five years typically taken to around half of that duration.
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