Every industry has been affected by COVID-19 and manufacturing is no exception. Competitiveness and cost-effectiveness have never been more important than in the current scenario. A 2019 survey noted that the average facility allocates approximately 9.2% of its annual budget for maintenance, and 20 hours a week (on average) is spent on planned maintenance. The traditional maintenance approach impacts the cost and productivity of the plants.
As per the press note released by the Government of India’s Ministry of Statistics and Program Implementation on Estimates of Gross Domestic Product for the First Quarter (April-June) 2020-2021, the GDP growth for April-June 2020 compared to April-June 2019 is -22.6%; the major contributors are manufacturing at -39.3%, mining and quarrying at -41.3% and construction at -51.4%. Though the negative growth in these sectors are due to factors beyond the control of the individual companies (i.e. the pandemic), it shows that any loss in efficiency or low reliability of equipment in these industries will hit the bottom line of the organisation, as these sectors are heavily dependent on machinery.
Even when the factories in India started functioning after the lockdown, there were restrictions on the number of people who can be present at any given time, which affected regular maintenance activities as well. To cope with the current situation and to keep factories future-ready, companies need to adopt advanced maintenance systems.
Smarter approach toward maintenance
The way maintenance has been conducted over the years has changed dramatically. Today, industries are not asking about reducing the breakdown and breakdown time; however, they are focusing on how the maintenance personnel and machines can identify the issues, analyse the cause and implement the action to prevent downtime. The change is being implemented by industries and is driven by various algorithms and tools with the help of Industry 4.0.
Preventive maintenance will reduce the breakdown to some extent, but it doesn’t cover various aspects of a machine, like machine parameters, product specifications, process parameters, etc. That is where predictive maintenance, the logical next step to the current preventive maintenance practices, comes in. Predictive maintenance traces the performance of the assets from the past and continuously compares it with the present state to avoid future breakdowns. More advancement in the system will also act autonomously on the root causes of breakdown or failure.
Advancements in industrial maintenance practices
The convergence of IT with OT is transforming the industry as a whole. Along with these advancements, organisations are moving toward digital enterprises and away from industrial organisations. Modern-age technologies, such as cloud computing, Big Data and Industrial Internet-of-Things (IIoT), are being deployed to enhance the scalability, reliability, effectiveness & cost-efficiency of machine and maintenance practices. The larger benefit, of course, has been derived in industries, like oil & gas, energy, manufacturing and aerospace. However, automotive, pharmaceuticals and several other industries are also leveraging the tools and technologies.
Maintenance is not restricted to just conducting the breakdown repair work but also includes all other aspects of maintenance. Some of the major benefits of advancements in maintenance practices are:
Use of Additive Manufacturing for the production of critical and discontinued spares
3D Printing is a boon for industrial maintenance, as it is now much easier to print an object that is commercially difficult to procure. The current disruption in the supply chain makes it difficult to procure spares or items from OEMs or any other supplier, so 3D Printing critical items is the most convenient and cost-effective solution for industries. Various companies are using 3D Printing to produce spare parts. There are numerous cases where an equipment failure could occur unless the part is replaced. In such cases, Additive Manufacturing can help produce the required part, eliminating the lead time previously required for procurement. This expedites maintenance activities and reduces inventory costs. There are several examples where an OEM discontinued the manufacturing of a particular part as the machine is no longer in their system; however, such issues are now being easily resolved with the introduction of 3D Printing. Printing a discontinued part increases a machine’s longevity while removing the need for an expensive replacement.
Use of Augmented Reality for technician training and remote maintenance
Augmented Reality (AR) is needed because of the increasing complexities in industrial equipment and machinery, which makes it increasingly difficult and expensive to detect, analyse and troubleshoot the problem to repair the equipment. AR can provide remote instructions for maintenance based on the skill level and understanding of the technician. It is also helpful in facilitating the training of technicians by OEMs, experienced technicians or industry experts in the particular field. Virtual Reality, along with AR, can also be used for training purposes.
Use of Big Data and cloud computing for data monitoring and problem analysis
Various sources, including the different types of sensors (e.g., vibration, acoustic and thermal imaging), help collect the data. This data can later be analysed by expert systems and sophisticated algorithms. Extensive use of sensors to monitor operational conditions, strong historical data and analytics form the backbone of any predictive maintenance approach. With cyber-physical systems becoming a reality and even discrete manufacturing systems collecting data directly from the machines, this will soon become the norm. Automated data collection eliminates the issues of error in data reporting. With this approach, IoT systems for data collection can seamlessly integrate with data analytics systems, saving additional effort and time.
The presence of AR, VR, cloud computing and Big Data allows continuing production, if there are any issues, by not only figuring out what the issue is but also providing the solution, which wasn’t possible before.
More integration of IT with OT
Maintenance has evolved over the years and will continue to do so going forward. As data monitoring and analysis become more intelligent, future implementation of maintenance practices will see more integration of IT with OT. The convergence of OT and IT will allow better-informed choices for decision makers. The use of a wide range of data sensors will allow vast data collection and real-time problems and solution identification. The skill upgradation will be imparted by various IT tools for personnel who will be able to run, maintain and manage the systems. These improvements will reduce costs in the long run and address barriers that hinder the implementation of successful maintenance practices. The pace of adopting advanced industrial maintenance in the manufacturing sector needs to increase or companies risk becoming obsolete.