Market trend Increasing operational efficiencies with predictive maintenance
The global market for predictive maintenance is expected to reach 11 billion dollars by 2022. On a global scale, Europe is considered to witness the most significant growth in this segment as the region has already lined up significant predictive maintenance solutions in the market.
What is predictive maintenance? As the name suggests, by implementing predictive maintenance one can predict and also maintain the functioning of their machines in a smart factory setting. Initially, factories suffered huge losses due to the failure of a particular machine or part as it led to production downtime. However, now with the advent of smart factories in line with Industry 4.0 and IOT (Internet of Things), one can implement predictive maintenance to track and even predict if a particular machine or part is going to break down. This enables the service team to monitor the machines in real time and be better prepared to replace a certain part or machine before it starts affecting or even stops the entire production line. Thus, predictive maintenance assists companies to increase their operational efficiencies, reduce costs and even eliminate production downtimes.
For instance, the leading car giant, BMW makes use of predictive maintenance for body shop robots, welding tools and drives in order to avoid unplanned system downtime. It is also used for materials handling in assembly which ensures long-term, reliable operations of their assembly line conveyor system over a number of years.
Growth of the predictive maintenance market
According to a report by Management consulting company, Roland Berger, the global market for predictive maintenance is expected to reach 11 billion dollars by 2022. Region wise, Europe will witness the most significant growth for this segment considering predictive maintenance solutions already exist in the market or are at an advanced stage of development.
A recent PWC survey that interviewed 268 companies from multiple industrial activities such as chemicals, metals, automotive, food production, electronics and paper in Belgium, Germany and the Netherlands mentions that about 11% of the respondents are already analysing the data collected via predictive maintenance for decision making. It also found out that as many as 60 % of the respondents are keen to implement predictive maintenance in the near future in order to increase their uptime.
Some of the core reasons behind companies adopting predictive maintenance include improved uptime; reduced costs; cutting risks associated with health, safety, the environment and quality; extending the lifetime of the assets and improving customer satisfaction.
Exploring predictive maintenance further, Rolls-Royce has come up with nanobots called ‘Swarm robots’. Via these bots, the firm aims at offering a better quality of engine servicing. The nanobots can access places that are difficult to reach by hand and are also capable of carrying out a visual inspection of the engine. Apart from this, the firm has also introduced mini ‘Inspect’ robots which are placed inside the engines in order to detect any maintenance issues.
SIA Engineering Company and Safran are also working on a predictive maintenance software for the aviation industry. Under the contract, Safran will help in developing and deploying software and services, while SIAEC will provide its expertise in engineering and maintenance, repair and overhaul.
Predictive maintenance is undoubtedly going to be one of the most vital concepts that will be implemented by factories in order to boost production and stay ahead of their competitors. So, when are you planning to install a predictive maintenance solution in your factory?