Maintenance in the era of 4.0 - it's still all about the people
03 July 2019
Sponsored by Festo, as part of Maintec 2018 Controls, Drives & Automation hosted a round table discussion on the development of Maintenance 4.0 systems for predictive maintenance. The event attracted a range of lively and knowledgeable attendees; chair Andy Pye shares some highlights of the insightful session
Few things can damage the financial stability of a manufacturing facility more than unexpected downtime. On average, manufacturers suffer with 30% or more downtime during their scheduled production time. In some industries, such as automotive assembly, downtime can cost up to £17,000 per minute (a mind-blowing £1 million an hour).
The penetration of advanced maintenance engineering practices within UK manufacturing is patchy. Many companies still operate a breakdown maintenance system and the available technologies are not being used effectively.
The penetration of advanced maintenance engineering practices within UK manufacturing is patchy
On the evening of the first day at Maintec 2018, and shortly after the close of the exhibition, we held a behind-closed-doors Round Table Discussion involving invited key senior maintenance specialists from users and suppliers in the engineering sector.
Around the Table
Andy Pye, Consulting Editor, Controls, Drives & Automation
Charlotte Stonestreet, Editor, Controls, Drives & Automation
Lee Hibbert, Consultant, Publitek
Richard Kelly, Managing Director, EMS Cognito (Presenter)
Steve Worth, Sales Manager, Klüber Lubrication GB (Presenter)
Jon Moody, CEO, SSG Insight
Prof Jyoti Sinha Programme Director, Reliability Engineering and Asset Management (REAM), University of Manchester
Andy Kidd, Chief Engineer, British Engineering Services
Phil Owen, Managing Director, SPM Instrument UK
Geoff Walker, Director, Faraday Predictive
Stephen Lewis, Consultant, Rail Technologies, British Steel
Nanoo Patel, Consultant Engineer, Tiara Machines and Systems
Karl Redmond, Associate, Rider Levett Bucknall
John Benjamin, Novotek UK & Ireland, Glasgow
Jon Hill, Business Development Director, INVMA
Lee Roberts, UK Sales Manager - Industry/Utility, DESMI
Marcus Halliday, Distribution Director, EMEA, Europe and Middle East, Cordex Instruments
The key theme we explored during the session was Overall Equipment Effectiveness (OEE). The discussion considered the effect on OEE of predictive maintenance, including the advent of Industry 4.0 devices, and how these concepts are being taken up by the SME community in the UK.
At the Round Table Discussion, Richard Kelly, Managing Director of EMS Cognito, set the scene, with a brief presentation on OEE.
OEE stands for Overall Equipment Effectiveness. It takes into account three aspects of the manufacturing process – Availability, Performance and Quality. The result is expressed as a percentage. An OEE score of 100% is perfect production: manufacturing only good parts, as fast as possible, with no stop time. An OEE score of 85% is considered world class for discrete manufacturers. Table 2 lists the six major losses which contribute to reduced OEE.
Industry 4.0 is ushering in a new approach to maintenance activities
Automated machinery can dramatically increase effectiveness by speeding up production time and reducing the potential for human error, therefore increasing OEE. The fourth Industrial Revolution (Industry 4.0) is ushering in a new approach to maintenance activities, offering as it does, the ability to measure parameters at the coalface, and pass that data, remotely if needs be, for analysis. How will digital technologies underpin continuous maintenance? The more data that is obtained over time, the more confidence can there be in the predictions made, and this helps with planning maintenance schedules and the logistics of having spare parts available at the right time.
Involving the Full Team
Andy Pye challenged the participants to discuss what are the barriers to making maintenance improvements happen? How easy is it to involve an operator/ What skills and training are needed?
Jyoti Sinha (University of Manchester) argued that the key is understanding how the machine works, and therefore involving the operator is vital. Despite automation and smart factories, people remain the cornerstone of the plant of the future. Concepts such as OEE can be seen as too abstract to operators working on the shop floor.
Despite automation and smart factories, people remain the cornerstone of the plant of the future
A good maintenance strategy is very dependent then on involvement of the whole team. At the beginning of the project the designers have a massive influence on overall life cycle costs, so most of the decisions that influence the reliability of an asset are locked in early in its life cycle, and at the operational phases there is less and less opportunity to influence the life cycle cost through maintenance related decisions. Sometimes 80 to 90% of the life cycle decisions about the asset may be committed, “locked in” before the equipment reaches commissioning.
At the operational end of things, decisions have already been made that influence reliability, maintainability, replacement life and essentially output or service levels.
Technicians should get involved in purchase decisions, suppliers in operational decisions, and service engineers in spare parts logistics and reliability improvement. Operators should be part of the maintenance planning and execution at the basic level.
Management’s job is to be close to employees to help them develop their skills. Good record keeping is essential, so regular record audits are needed to check on quality. Maintenance workers tend to be hands-on people, so they are not always enthusiastic about completing piles of paperwork.
The goal of digitisation is to improve agility and responsiveness at strategic points in the process: tracking components for maintenance, managing consumption (raw materials, energy, etc.) and ensuring traceability of parts right to end users. It covers all areas of the plant.
The digital revolution supports and connects management at all levels. From employees to plants managers, everyone benefits from new technology. Digital technology aims to provide tools based on how things are really done on the job. The tools make work easier. They are more connected and collaborative, easier to use and more mobile – in short, more efficient.
These changing roles for the maintenance function mean that the skillset required for the maintenance engineer has changed, with new skills required, and some older ones - arguably - less important. As in all engineering disciplines, and in the light of proposed changes in the political landscape, the UK faces acute skills shortages.
An additional difficulty faced by some sectors is that these skills – typically science, engineering, and technology related ones - are in high demand in other sectors, and therefore it needs to identify how it can develop its own talent pipelines if it is to match performance levels in competitor countries.John Benjamin (Novotek) observed that the input of operator observation remains extremely important alongside the sensors and systems of Industry 4.0. Human data forms a big part of the data set. But human failings are also important, so can be enhanced by the use of phone apps. QR scanners can be used to transmit a grease code, for example. This is not advanced machine analytics, but basic stuff, even though the data can be transmitted via the cloud using Industry 4.0 methods.
Worth commented that such aids free up the engineer to do other maintenance tasks. We need to upskill operators, despite techniques like colour coding and mistake-proofing generally. Today, auto-lubrication is often employed to minimise intervention, and records kept of the “what, where and when”. Comments about noises, smell and vibration are really important and all operators come equipped with two eyes, two ears, a nose and a mouth – perhaps the best condition monitoring sensors of all!
Benjamin said that people should not expect a magic show from condition monitoring. It will give you some benefits, but people are absolutely vital. An analogy is the car driver, who will check oil, water, lights and tyres, alongside the need for regular MoTs and services. Most failures come with some sort of warning. Operators know when something is going wrong.
However, he added, while people often think that what they are doing now is the best they can do. This mentality would have us flying Sopwith Camels!, But machines have no agenda, and unlike people, their data can be used for engineering, financial or reliability purposes. Equipment such as spinning devices often show signs of failure long before you can detect them with eyes and ears. Industry 4.0 is the means of getting machines to yield their information. Then the financial director can see the beneficial impact of condition monitoring on the machine.
It is vital to get people to think "can we be better" - how do we know how good we are compared to our competition? In the post-Brexit world in full glare of global manufacturing with China, India and elsewhere, people who have lower costs bases or are simply smarter and have better products will have a major advantage.
In practice, the takeup of risk-based inspection is not where it needs to be, even though pressure systems regulations allow for it. Lifting equipment rarely uses it, preferring instead 6 or 12 month maintenance intervals.
Sinha agreed that Industry 4.0 gives the platform, but education and understanding of the machine is still important – the ability to look into a machine to find the reason for a failure. That local level of machine knowledge is still important. Machines themselves are becoming smarter and can teach industry professionals themselves, but operators still struggle with some elements, including software changes, where training is still needed.
Nanoo Patel (Tiara Machines and Systems) took that point further by referring to the “us and them” barrier to knowledge sharing. In his experience, operators are often pushed aside, and can equally hang onto information they know, despite knowing the machine best. It is important to give the “ownership” of the machine to the operator – make it up to that person to call for maintenance. This approach works brilliantly, and is much more effective than the responsibility falling to somebody sitting remotely and trying to play with data.
Sinha agreed. “This is 100% right - to do the maintenance you need to know *what* and *where* to put the maintenance, not rely on trial and error.”
Benjamin also agreed. “Industry 4.0 is knowledge-heavy at all levels,” he stated. “You have to know what you are doing, even to torque a bolt or apply a grease. You can have a smart tool which shows what it was taught to do. Even operators on equipment like GE’s aviation gas turbines, which are instrumentation heavy, need to know the fundamentals of fluid dynamics, thermal engineering, and the materials of construction. Machine learning is not replacing people, but about giving them better tools and better information to find out what happened immediately before or is about to happen.”
He drew the analogy of a smart phone – Siri and Alexa and the others cannot think originally outside the box like human beings can. They cannot manipulate and use knowledge like human beings. So Industry 4.0 is a human revolution, not a machine revolution.
Lee Hibbert interjected and asked how we should take people forward. By taking all this data off a machine. will operators end up drowning in data. How difficult is it to democratise that data?
Redmond said that the key issues are what information, what questions, how is it captured, what will be the cost, how long will it take. Not all people in senior management positions have the cultural nous to pass responsibility down the chain. People both at the top and bottom have to understand what this is for, and if they do, 99% will buy into it.
Hibbert asked if the age profile within engineering is a barrier in being able to break down that cultural issue. Redmond agreed: “Culture comes with so many problems at the top of the tree – we need to start joining up the dots and benefits.”
Charlotte Stonestreet asked if this cultural problem is a British issue. If we compare investment on automation and Industry 4.0 in the UK compared to other countries, including the EU, we seem reticent to make the leap.
Jon Moody (SSG Insight) quoted research he had done with Sheffield Hallam University. “Post-Brexit we will be operating in a global world and we will be exposed to a much wider cultural change – Industry 4.0 data is an enabler in the way we do business – something we will need to compete as an engineering country with China and India. These countries do not have the cultural heritage (or is it baggage?) of our organisation cultures and they can start with an open mind. Karl Redmond is absolutely spot on – we can meddling around in operational issues, but success is fundamentally down to how we make the organisation work better.”
Patel said that if we are not very careful, Industry 4.0 can blow up in our face - how do you sell it to the ground level? It is in danger of being regarded as another Big Brother – a disease in British industry of pitching productive against non-productive. We must not be afraid to give the individual some responsibility and pay for it at the ground level. Slapping monitors on the shop floor and having them operated by the guy sitting in the office is not the way forward.”.
He added that we must help companies to be competitive. My best customers are those where the operators on the shop floor love the machines. Management must be open and honest or a level of mistrust will emerge.