Maintenance has always been a strategic concern for Industrial Equipment Manufacturers and Manufacturing Enterprises. For Manufacturing Enterprises maintenance and asset repairs consume vast amounts of resources, eat deeply into operational costs, and present a serious impediment to efficient operations. A single hour of downtime alone can cost a large enterprise over $200,000 in productivity losses. For equipment manufacturers, this means higher field service costs, higher customer service center costs, lower customer satisfaction, and a distinct disadvantage over competition.
For years, Manufacturing Enterprises and Industrial Equipment Manufacturers have followed the reactive or time-based maintenance approach but with the advent of Industry 4.0, also known as the Industrial Internet of Things, there is a new trend i.e. Predictive Maintenance.
Now, let’s take a look at the disadvantages of reactive or time-based maintenance approach before delving into why Predictive Maintenance is the need of the hour.
Time-based Maintenance or Reactive Maintenance
In this approach, the age of the machinery defines the maintenance schedule plans because older equipment needs more frequent maintenance. There are several problems with this approach. For instance, past data has shown that 18% of equipment failures are due to age-related reasons while 82% of equipment failures have a more random pattern. Another report suggests that 30% of maintenance activities are carried out too frequently. Here are some scenarios of the problems of this approach in Repair, Field Service, and Customer Satisfaction:
Therefore, it is quite clear that Predictive Maintenance is the way forward for the Manufacturing industry. Let’s explore the benefits and types of Predictive Maintenance.
Predictive Maintenance
Predictive maintenance refers to a maintenance process that is based on the evaluation of real time equipment data attained from sensors to gain visibility into the current condition of the equipment. This information can be used to deliver needs-based maintenance to reduce downtimes, increase equipment uptime, and improve overall customer satisfaction. The field service agents are given work according to data from sensors that indicate an asset’s health with complete information about parts and tools required to perform repairs and only acting based on the probability of an outage.
Benefits of Predictive Maintenance
Types of Predictive Maintenance
Enterprises start with Rule-based Predictive Maintenance and then switch to Machine Learning-based Predictive Maintenance.
Impact of Predictive Maintenance on Business Models
Predictive Maintenance will allow companies to start selling Industrial Equipment on a subscription basis, like software-as-a-service (SaaS). This is referred to as the servitization model where the user pays for the uptime of the equipment and the equipment manufacturer’s job involves servicing and replacing the equipment with minimal to zero disruption.
Service contracts, too, will become less about the frequency of maintenance and more about equipment uptime. Basically, the industry is moving towards a system where businesses are fixing problems before the customer notices or points out that something might be wrong.
IIoT enabled manufacturing equipment is the key to enabling Predictive Maintenance. Industrial Equipment manufacturers should make IIoT enablement part of their new product development process but when it comes to legacy non-IIoT products, which have already been installed, there is a problem. To solve this problem, equipment manufacturers can offer aftermarket IIoT enablement solution to their customers where the existing equipment can be retrofitted to enable Predictive Maintenance.
Sasken with its deep expertise in communication technologies and multiple solution accelerators across the IIoT value chain such as IIoT Sensor Kit, IIoT Gateway reference architecture, IIoT Analytics platform and a use case solution accelerator for Predictive Maintenance can help equipment manufacturers with: