Predictive Maintenance helps reduce almost half the maintenance cost
Published by : Industrial Automation
Titli Chatterjee, Manager – ER&D Industry 4.0 Research, NASSCOM.
Maintenance is a critical aspect of industry – how do companies decide their maintenance strategies?
As the pandemic disrupts the industrial growth and pushes the companies into economic uncertainty, some of the regions impacted are major production and manufacturing hubs, playing a pivotal role to the sector’s global chain. Though there are disaster management or contingency plans, taking quarantine plans into consideration was out of the proposition. Few of the scenarios to be under the intention for a faster recovery from such incidents would be the regular standards. Now, I am talking mostly for the medium and small enterprises:
1. Workforce management being top of the concern – Social distancing, going through a health screening including temperature check, extensive sanitization along with face masks that would be reusable and well-fitted. Not the easily available regular surgical masks.
2. Testing should be a regular affair, so enterprises and plants would be well prepared with the testing kits.
3. Bringing an online system to record employees if they are symptomatic or have been in recent contacts with people diagnosed with Covid-19.
1. While the industry talks about supply chain distortions and procurement aspects, a careful consideration would be on the disruption as the catalyst for change.
2. Exploring intersections of enabling technologies with a fine blend of foundation technologies and disruptors would be the key.
3. Technology coupled with adoption strategy addressing the immediate pain-point the company is facing would drive the road-map – For example while analytics would enable the data architecture and insights, cognitive automation would help in reimagining engagement, driving a broader business intelligence (If at all the company is prepared!)
4. Other plans should aim to address the combined challenges of reduced production volumes caused by supply chain and declining consumer demand and minimising errors aiming cost reductions.
Why do companies still rely on corrective maintenance despite other options?
Despite developments in equipment and facilities most of the companies prefer sticking to conventional maintenance needs. The underlying problem with corrective maintenance is the cost implications, since no preventive actions are taken for medium or high priority assets. Thus, unplanned downtime and unexpected stoppage may lead to huge repair costs. Among firms currently experiencing a rapid decline in revenues and charting a recovery path, a data- derived condition monitoring generating alerts for bad trends and inspections would be more beneficial than other maintenance strategies.
Has predictive maintenance become easier to implement in the IIoT era?
With the emergence of Industrial Internet of Things (IIoT), blend of huge data volume and analytics enable improved maintenance strategies to progress along the maturity continuum. Predictive maintenance is one such application which helps in detecting advanced warnings before failure. IIoT enabled monitoring combines different datasets or small data from a device with algorithms to monitor the condition of a machine and raise an alert. This also works on virtual equipment (digital twins) that help in saving a great deal of cost.
How important is inventory management for a successful maintenance strategy?
Inventory management is one of the major issues in the production process, thus it is essential for the maintenance teams to have a clarity on the inventories before they participate in the monitoring of the equipment. With just-in-time production stocks are reduced to minimum. Thus, maintenance pertains to fewer repairs and monitoring, adapted to the production line
With emerging technologies like AI & ML now coming into play, is Zero Downtime now with sight?
AI/ML will have a huge impact on manufacturing and unleash a significant part of disruption. This will gradually help to provide prescriptive solutions to production issues, addressing zero waste concerns and least amount of time would help in suggesting what’s possible. However, a robust data infrastructure needs to be at place to obtain real AI/ML. It also leaves the manufacturers confused on the right adoption of technology exactly aligned to the pain- points.
As the world battles the Covid-19 pandemic, will maintenance call for altogether different strategies?
The Covid-19 creates a great deal of chaos at the industrial front. Majority of the companies feel extreme urgency to cut costs and eliminating maintenance due to less production is an obvious concern. The need of the hour would be involving near-zero unplanned downtime for critical assets. Since the production system is intertwined with all the machines/tools and the assembly line changeovers, without maintenance it would create more disturbances in the production line. This would require return to recovery and upgrading the existing maintenance strategy. Predictive maintenance through huge volumes of incoming data, even the minuscule data set derived from a machine would be of utmost importance. Research indicates that Predictive Maintenance (PdM) helps to reduce almost half of the maintenance cost of an equipment. Predictive maintenance can help avoid the random failures as maximum assets have a tendency to exhibit a random failure.
Titli Chatterjee has been leading the ER&D/Industry 4.0 research initiatives of NASSCOM, having experience in research and consulting in the areas of emerging technologies and engineering services. In her current role as Manager – Research Titli is closely working with industry leaders, startups and other stakeholders to highlight how technology can be a game changer on the industrial front, and developing a roadmap in disruptive technologies for Indian IT-BPM industry.