Productivity Performance & Profitability Through Maintenance 4.0
Introduction:
Is Maintenance efficiency and effectiveness still a challenge for most industries? It seems so. McKinsey tracked maintenance performance across the most technologically advanced companies like offshore platforms, navy and military aircraft maintenance over a ten year period (2012 to 2021).
What did they find?
They found that the trend of average scores on maintenance effectiveness achieved by these companies who have adopted relatively advanced maintenance practices’ remained simply flat. No improvement was found in reducing maintenance costs, increasing uptime, reducing failures and reducing unplanned outages.
Across all industries this lack of progress is evident and that is a matter of real concern, especially when there is an intense pressure on industries to improve their Return on Assets and Return on Capital Employed, specially after being affected by COVID pandemic, which unfortunately cannot be done without improving maintenance engineering to eliminate or reduce failures.
The pressure is so high that US Navy is willing to pay more to manufacturers of Light Amphibious Warships who guarantee reduction of failures and unplanned outages of their warships.
So, do industries need to try out something new?
Not necessarily.
Good Practices:
Good practices that drive maintenance performance are well known though not practiced rigorously. Some of the good practices are as follows:
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CBM: Condition Based Maintenance (CBM) was developed in the 1970s and had kept evolving by introducing new techniques of prediction. However, I feel that the prognosis part of CBM is still not practical or well developed. Whatever it is, I consider this as a fundamental pillar of Maintenance Engineering. However, Predictive Maintenance is not to be equated to CBM though it plays a vital role in CBM.
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RCM: Reliability Centred Maintenance (RCM) was developed from 1980s to counter the risks of failures by taking care of its consequences. It has found its way into industries, where CBM forms the keystone of RCM practice. One of the important contribution of RCM is that it delineates failure patterns into six distinct patterns, where the sixth pattern (infant mortality) is the most prevalent across all industries. That is 68% to 90% of all failures falls in this pattern. The concern is that there are no objective and well developed methods to address this common and dominating failure pattern other than employing predictive maintenance. Though predictive maintenance, when applied correctly detects failures in time, it fails to bring down the failure rate to an acceptable level.
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RBI: Based on RCM, Risk Based Inspection approaches matured during the 1990s and are in use in petrochemical industries. It is used for assessing the condition of static equipment.
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MP: Though Maintenance Planning and scheduling have been around for decades and is widely used through the application of Computerised Maintenance Management system we are still not sure how to optimise the planning system and use it to achieve the three general objectives of Maintenance Engineering — a) reduce cost b) reduce failures c) eliminate unplanned stoppages.
- IOT and AI: Presently, this technological strategy is attracting a lot of interest. This is basically an enhancement of Predictive Maintenance with a liberal dose of Artificial Intelligence that aims to predict faults quickly, accurately and well in time and eliminate the human element in maintenance engineering. Advanced analytics techniques aims to forecast failures using information sources and data that were not previously accessible, or even available or unsafe to collect with hand held data collectors. Therefore, it is now possible, for example, to combine information in shift handover reports, production schedules, and even changes in the weather to predict when equipment failures are likely to occur. Industry 4.0 or Maintenance 4.0 is a catch-all term for a big range of technologies and approaches, including the networked sensors and devices that make up the Internet of Things, big data and advanced analytics approaches, and new digitally-enabled manufacturing techniques. Many of those things have potential applications in maintenance. That could have a huge impact. We know from experience that implementing a predictive maintenance system can reduce production losses by more than 20 percent while also cutting maintenance costs by over 10 percent. So by using this advanced version of Predictive Maintenance can we hope to better existing baselines to justify return on investments?
With the implementation of new technology, the revised realistic and achievable goals can be— a) 50% reduction of maintenance costs from their present level b) 80% reduction of failures c) sustained uptime of 98% or above and d) 100% elimination of unplanned outages. Though early, such achievement through the application of new technology of AI based IOT, in its present form seems unlikely.
Why?
Discussion:
The important insight from the above discussion is — the fundamental conundrum in the maintenance engineering still remains unaddressed that is — what do you do about the dominating Type 6 failure pattern (infant mortality) which have three fundamental characteristics — a) randomness b) infant mortality and c) non-linearity? Preventive maintenance/IOT/AI cannot address all the three characteristics. Though CBM and Predictive Maintenance do address the first characteristic that is – randomness it does not address the other two characteristics. The only strategy that would address this nagging puzzle of maintenance engineering is a combination of precise application of CBM with a reasonably accurate Prognosis (overcoming the challenge of the third characteristic -‘non-linearity’) and DOM (Design Out Maintenance). Though CBM is very well developed, Prognosis and DOM are still in their infancy. That is unfortunate.
However, there are other constraints that need to be addressed before implementing the new technology of IOT, such as:
1. Data: Accuracy of equipment data, equipment history data, detailed data on historical downtime, trend of asset performance, trend of condition of the assets, process data, and linking of different types of data for effective prognosis — without which deep analysis and strategising isn’t possible. Unfortunately, accuracy availability of such data along with manpower resource to critically examine data are lacking in most industries.
2. Planning:The insights from the analysis and strategising are to be backed up by equally robust processes of CBM, Planning and Scheduling, Spare Planning and Quality Workmanship. For most industries gaps exist in these processes, which are difficult to fix quickly.
3. RCM: Without proper development of CBM, Prognosis, DOM through RCM process, massive technological intervention of IOT is surely headed for failure. The fact is CBM, Prognosis, DOM and RCM can’t be outsourced like many other organisational processes since these processes form the core of modern maintenance engineering practice.
4. Management: Very often management is a great hurry to accomplish the desired goals. It is indeed tempting to try and introduce new analytics and IT tools in a “big bang’ way like an ERP system implementation. Unfortunately, ‘big bang’ approach does not work in Maintenance Engineering. We can’t apply technology in a vacuum and expect great results.
Why is that?
This is because Maintenance Engineering would always involve significant amount of human element and application of human consciousness for it to be successful. I don’t see how the human element can be eliminated by IT tools and techniques, which Maintenance 4.0 envisages.
Hence, a sure and safer way to introduce advanced maintenance technology is the time honoured “pilot-and-rollout approach”. This is because it takes time to develop and hone new skills and new ways of measuring performance and new ways of seeing and working. Usually the ‘pilot-and-rollout approach’ is followed by large-scale maintenance and reliability transformation during the “roll out” stage, which is generally fast paced, only if the “roll out” is supported by appropriate stream of value added knowledge and fine tuned analytical process.
Conclusion:
In my experience, ‘pilot and roll out approach” is the only sustainable way to drive organisation change through Maintenance Engineering 4.0 to bring about significant changes to transform business results on an on-going basis with minimal effort.
References:
1. What Industry 4.0 can do for Maintenance https://www.mckinsey.com/business-functions/operations/our-insights/ask-an-expert-what-industry-40-can-do-for-maintenance?cid=soc-web
2. Navy willing to pay more for maintainable ships : https://www.defensenews.com/digital-show-dailies/navy-league/2021/08/04/navy-willing-to-pay-more-for-more-maintainable-ships/#.YQuF1xDGCqs.twitter
3. Thermodynamic Degradation Science by Alec Feinberg, 2nd Edition, 2019, DfRSoft/Wiley
4. Complex System Maintenance Handbook Editors- Kobbacy & Murthy, Springer, 2010
5. Design in Nature, Adrian Bejan & J. Peder Zane, Anchor Books, 2013.
6. Irreversible and Reversible Degradation httpsrmcplrapid.com/2021/08/03/irreversible-reversible-degradation/
7. Impact of R&M Improvement through DOM httpsrmcplrapid.com/2021/07/15/impact-of-rm-improvement-through-dom/
By Dibyendu De, Director, RMCPL, 6th August 2021
Impact of R&M Improvement through DOM
Author: Dibyendu De, Director, RMCPL, Kolkata, India.
Abstract:
The use of the terms Reliability (R) and Maintainability (M) are now in vogue. Does improvement in Reliability and Maintainability (R&M) relate to Maintenance Optimisation or Asset Optimisation? In this paper we would examine whether such a relationship exists. We would also explore whether the DOM (Design Out Maintenance) strategy can be effectively employed in improving Reliability and Maintainability (R&M) of an industrial facility or engineered systems in order to achieve the twin objectives of profitability and sustainability.
Introduction:
First let us state the definitions of Reliability and Maintainability. Then let us expand on what is actually meant by Maintenance or Asset Optimisation.
Reliability — “The probability that an item will perform a required function, under a stated condition for a stated period of time.”
Reliability is therefore the extension of quality into the time domain and may be paraphrased as the ‘probability of a non-failure in a given period of time.
Maintainability — “The probability of repair in a given time.
Expanding on that, Maintainability means the probability that a failed item will be restored to operational effectiveness within a given period of time when a repair action is performed in accordance to prescribed procedures.
Maintenance Optimisation or Asset Optimisation:
The idea of an optimised maintenance program suggests that an adequate mix of maintenance strategies and actions needs to be formulated and fine tuned in order to improve uptime and extend the total life cycle of the physical asset and assure safe working conditions while bearing in mind limiting maintenance budgets and environmental legislations. This does not seem to be straightforward and may require a holistic view. Therefore, a maintenance concept for each installation or factory it is necessary to plan, control and improve the various maintenance strategies, actions and policies as applied to that installation within the given constraints of time, manpower, skills, kowledge, budgets and legislations.
A maintenance concept or strategy may in the long term even become a guiding philosophy for a facility to performing maintenance/engineering. In some case, advanced maintenance strategies are almost considered policies on their own. What is certain is that maintenance strategies determine the business philosophy concerning maintenance and engineering and they are needed to manage the complexity of maintenance per se. In practice, it is clear that more and more companies are spending time and effort determining the right maintenance concept and strategies applicable in their context.
Maintenance Strategies
The usual mix of maintenance strategies that are used for Maintenance/Asset Optimisation are RTF (Run to Failure), TBM (Time Based Maintenance), UBM (User Based Maintenance; also known as Opportunity Maintenance), CBM (Condition Based Maintenance), E-Maintenance and DOM (Design Out Maintenance).
At present, RTF, TBM, UBM, CBM and E-Maintenance accept the inherent reliability of the physical asset, which they intend to maintain as a given fact. The governing concept is that once a machine is designed, manufactured and installed the upper limits of reliability and maintainability are fixed and can not be improved upon during the operational stage. This is true to a great extent. However, such implicit acceptance effectively limits the upper limits of productivity, performance and profitability of a manufacturing facility. Hence, maintenance, as usually practiced, will fail to sync with the constant market pressure of improving productivity, performance, profitability and sustainability. Failure to do so can often force a company out of business or settle for lower profits till new or additional equipment are purchased to meet desired business goals. Clearly, this is a costly proposition even for cash rich companies.
The alternative lies in innovating or making greater use of DOM (Design Out Maintenance) strategy on a given set of physical assets considering the operating context of a facility. DOM — instead of considering a system as given, looks at the possible changes (usually small innovations) or possible measures needed to avoid or minimise maintenance in the first place. Adopting a DOM policy implies that maintenance is proactively involved at different stages of an equipment life cycle to solve problems of failures or solve problems that prevents an organisation to achieve its business goals. This may be either done at the procurement stage or after the installation stage, when a machine is in operation. Therefore, it is prudent to apply the DOM strategy both at the procurement stage and at the operating stage to get the best benefits.
Ideally DOM strategy intends to completely avoid or minimise maintenance throughout the operating life of equipment. Though it may appear on the surface to be unrealistic it is completely possible to do so. One approach will be to consider a diverse set of maintenance requirements at the early stages of equipment design during the procurement process based on available knowledge of potential failure patterns and problems studied against business requirements. The other approach will be to consider the behaviour of the equipment during the operating stage and eliminate, avoid or minimise possibilities of failures through simple modifications/innovations on existing equipment.
As a consequence, equipment modifications along with process modifications and modification of maintenance processes are geared either at increasing reliability by raising the MTBF (Mean Time Between Failures) or improving maintainability by lowering MTTR (Mean Time To Repair). This may be done in various ways. In some situations, both MTBF and MTTR are to be addressed simultaneously. Per se DOM aims to improve the following:
1. Equipment Availability by extending the MFOL (Mean Free Operating Life),
2. Production Capacity by minimising unplanned downtime,
3. Safety (by eliminating the consequences of failures and reducing failure rates),
4. Extend the total life cycle of an equipment (by using an equipment for the maximum possible years)
5. Life Cycle Costs (LCC) by minimising maintenance costs
6. Sustainability through optimised use of resources to run the system at the best operating condition.
In all the above cases it is imperative to lower or effectively contain the failure rate, potential hazards of an equipment and minimise loss or excess use of resources.
Modifications (usually small innovations), which lie at the heart of DOM may include the following (not an exclusive list):
- change of dimensions and material flows
- change of material
- change of condition of surfaces, structures and interfaces
- change of ergonomics
- change of maintenance process, planning and procedures
- change of designs, controls and knowledge
- change of items and parts, lubricants and redundancy
- change through effective scaling
- change in use of resources
- change in set ups, speeds, and operational processes
- change of environment, reactions and interactions
- change of thermal and energy flows
However, adoption of DOM strategy does not exclude application of other available strategies in the whole process of improvement. Judicious application of all available strategies is often necessary to achieve the business goals of a manufacturing facility for which a completely new process has been developed, which critically focuses on improving Reliability and Maintainability of a facility. Finally, it depends on the how the DOM projects are formulated, implemented and managed across a manufacturing facility. Here agility and constancy of purpose are two critical management factors that would determine the quality of the results — profitability and sustainability, which effectively translates to lowering the Total Cost of Ownership of facility, which is the essence of Asset or Maintenance Optimisation.
