Increase productivity with enterprise asset management cloud and data analytics tools
Companies of all sorts, particularly those working in physical plant-intensive markets, need to keep up with their equipment to understand maintenance needs, optimize process efficiency and, ideally, get more productivity for less money.
The practice of doing those things falls under the umbrella of enterprise asset management and the rapidly developing Industrial Internet of Things has a lot to offer by way of support. Assets, or things in this case, produce a wide range of operational data that, if analyzed properly, can lend insight into lifecycle, efficiency and performance.
The Institute of Asset Management provides some commentary on the discipline: “At the simplest level it means an organization is making the best decision it can about its assets based on a clear understanding of its long-term objectives and purpose. The plans that are made for each asset are always part of a bigger picture. Decisions are only as good as the information they’re based on.”
In a world of ever smaller and cheaper sensors equipped with various types of connectivity, asset data can be harnessed to make better decisions about management.
IBM is a big player in this space with a product offering called Maximo, which is designed to enable avoiding unplanned downtime through predictive maintenance, maximize resource scheduling, reduce stock outs and use data to predict performance, according to the company.
“At the end of the day, we’re talking about more data from our machines,” IBM VP of Offering Management for the IoT Solutions business said.
“What can we do with that data with analytics, through mobile apps, other things? If you have more insight into how your assets are working, you can run it better, engage your customers differently, maybe disrupt your supply chain.”
To give an example, tire manufacturer Michelin uses the Maximo platform to share information between 70 factories around the world that typically run 24 hours a day, seven days a week, between 340 days and 350 days per year.
Ken Bodine, Maximo deployment leader for Michelin, said the solution gives the company a “competitive advantage” by letting a distributed workforce share asset information.
“We want to improve the reliability of our equipment and reduce our reactive maintenance,” Bodine said. “When one plant makes an advancement, it was difficult to share that advancement with another plant because the systems weren’t connected. We have standardized those processes, we have standardized the data reporting and we have standardized the indicators reporting.”
He said Michelin realized a 5% increase in efficiency based on internal metrics in six months after deploying Maximo.
The analytics engines required to store and process data, as well as make it available to users around the world, depends on cloud computing, another important aspect of enterprise asset management.
Software-as-a-service provider Fracttal specializes in cloud platforms for enterprise asset management.
The advantage of cloud computing, the company says, is “access to the creation of working groups and the assignment of custom permissions from anywhere in the world. IT will also permit access of clients and suppliers that can provide feedback on your information instantly.”
Fractal’s solution is “designed to help enterprises make optimal use of business assets and enhance objectives through the collection and organization of all necessary information, promoting informed decision-making and aiding in the generation of maintenance plans and tasks.”
Bringing Industrial IoT solutions to bare on enterprise asset management creates direct business value by using near real-time data to identify problems proactively and find the efficiencies that come along with reducing downtime.
