Internet of Things, or simply IoT, is basically meant to identify any potential failure and solve it prior to something grave happening with equipment used in the field of manufacturing. Some of these issues can disrupt vast systems almost entirely, and that makes IoT a pressing issue in many cases.
There are quite a few areas that manufacturers focus on when it comes to predictive maintenance running off of the benefits of IoT. It goes without saying that these are the ones which often serve up the biggest challenges when something actually does go wrong. Manufactures mainly use IoT systems in order to acquire better stability, cost savings, and equipment efficiency. Writer Kayla Matthews has opined that this minimizes downtime, and also takes out predictive analytics driven by data analysis, effectively bringing down the amount of speculation involved in preventative maintenance strategies. According to Matthews, it enables engineers to set up and start repairs even when a problematic machine is offline.
Based on the reports of Deloitte & Touche, around $50 billion is lost each year by industrial manufacturers in unexpected downtime costs. A rough 20% drop is seen in the productivity rate on account of poor upkeep. In that way as well, predictive maintenance will always be a crucial factor in manufacturing. Massive amounts of data flow are needed for implementing a predictive maintenance strategy. It is to and from IT experts, various business units, and teams that this data flows. Whole new analytics technologies are adopted and used by manufacturing companies for this very purpose. These companies are either adopting preprogrammed technologies along with their necessary analytics, or applying their own expertise in the area. An array of systems comprising applications, infrastructure, and sensors is employed for just the collection of data. This process makes use of different data formats and various communications protocols.
Meanwhile, data analytics company Spunk Technology notes that organizations may be provided with multiple technologies on a frequent basis by technology vendors, whether on an on-site or per-project basis. They also add that swivel-chair integrations and data silos will result from these factors.
Right from the implementation stage, organizations are sure to face technical and integration issues brought on by preventive maintenance systems. Such issues can be averted by implementing a better planned preventive maintenance solution, after considering the requirements of each organization.
Care has to be taken while choosing those precise technology solutions which bring the required support for the working of the system which comprises of appropriate documents, skills, people, and tools. A change management evaluation is also critical, so as to ensure that personnel has better motivation for sticking to an implemented system. It would be strenuous for highly trained employees who have become entrenched in existing operating procedures.
According to a report by Bain & Company consultancy, it company workers who have been introduced to IoT should probably move towards scalable solutions. After that course, they should be asked to deal with particular roadblocks that comprise IT, operational technology integration, and security. In the report, Michael Schallehn had stated that in IoT, a competitive edge would be formed when benefits of industry experience are not assumed by vendors. In order to fill the gaps between capabilities and knowledge, vendors are advised to partner with industry specialists and analytics firms.
Results from studies done by Amazon Web Services back the view that partnering with analytics companies would help workers function better if they have been introduced to new preventive maintenance solutions.
