Predictive Maintenance is Great, So What Are We Waiting For?
One of the most talked-about topics in maintenance and asset management is Predictive Maintenance (PdM), a condition-based asset maintenance approach that involves using sensors to measure the status of an asset over time while it is in operation. Especially with the developments in Artificial Intelligence (AI), it allows for the establishment of trends, prediction of faults, and determination of the remaining lifetime of an asset.
The enthusiasm for PdM is easy to understand when you look at the potential benefits. It essentially eliminates the blind spots, provides earlier detection and allows for optimal planning of corrective actions. Through PdM, manufacturers and industrial companies report that they can improve operational efficiency by achieving savings on scheduled repairs (12%), reduce maintenance costs (nearly 30%) and experience fewer breakdowns (almost 70%). The potential upsides are huge, especially in industries where margins are thin and operational efficiency is paramount. One would expect that with these benefits, the enthusiasm would be reflected in the market, however this is not the case.
In a recent survey conducted by PWC of industrial facilities in the Netherlands and Belgium, only 11% of the respondents had successfully implemented PdM in their facility in some form or another, with the majority still relying on having specialists do periodic manual inspections of the assets. With the recent global events further highlighting the problems inherent to this approach, we need to understand why there seems to be a hesitance for the market to adopt a solution that presents such clear benefits. What are the other 89% waiting for?
In a 2019 industry report, 5 factors were highlighted to be driving the demand for an industrial condition monitoring system solution.
Reduction of Downtime
Facilities are aware and actively looking for solutions to minimize downtime in their facility.
Expanding Scope of Use in Respective End-use Industries
Due to growing and changing needs and applications in end-use industries, demand for solutions able to meet their specific industry’s needs is growing.
System Safety and Reliability
Robustness and safety of the primary quality criteria — a system that will not cause issues in their facility in addition to preventing them.
The primary concern of consumers is customization, because assets, usage and environments vary from use case to use case, the need for a highly flexible and adaptable solution is key.
Because monitoring systems require a lot of initial capital investment and trained professionals to operate, end consumers prefer to procure services instead of directly purchasing systems.
Delving deeper, in a survey from Bain & Co. of more than 600 High tech executives have revealed Integration Issues to be one of the major concerns. As companies in the industrial sector have invested in more proofs of concept, implementation was found to be more challenging than they anticipated. Concern over integration issues — technical expertise, data portability and transition risks — was one of the biggest challenges.
While these concerns may vary from industry to industry, the hesitance for adoption becomes more understandable. For our industry to progress and realize the promise of Industry 4,0 where ‘machines asking for help on their own’ across the industry, these are the challenges we need to address. To be a successful PdM provider, and help their clients reach their long-term goals, industrial IoT vendors should be helping their customers overcome these barriers to adoption. And that is our mission at OneWatt, remove all the hurdles in adopting PdM for industry. Next time, we will be discussing how OneWatt is doing this.