News & Updates
April 16, 2021
April 14, 2021
Effectively managing asset performance has been an unrealized opportunity for asset-intensive industries. As a result, industrial downtime caused by equipment and process failure in just about every industry is still causing an ever-increasing and significant impact on manufacturing EBIT, production, and quality.
Assets and equipment are not being replaced or maintained optimally as they should be, which results in higher risks, larger costs, and adverse impacts on balance sheets. As we emerge from this terrible Covid crisis, this trend of “sweating the asset” is becoming more and more prevalent
Managing asset performance is a foundational capability for asset-intensive industries as they seek to make their operations more efficient, reliable, and safer. However, many organizations still see asset management as simply keeping track of asset data or more advanced maintenance, leading to several siloed applications and failing to demonstrate clear business value. In fact, fewer than 5 percent of companies have achieved an asset performance program that helps to optimize maintenance, operations, and asset investment decisions to achieve financial results. (can you add the source of this data?)
“The way we look at manufacturing is this: the U.S.’s strategy should be to skate where the puck is going, not where it is.”—Tim Cook, CEO, Apple Inc.,
Yet too many businesses are stuck with where the puck is – in terms of siloed views of the current state of asset data in form of graphs, charts, reports, and dashboards.
As we enter a new age of value creation through Industry 4.0 technologies, opportunities to take asset performance to the next level emerge through connected assets, the Industrial Internet of Things (IIoT), and artificial intelligence and advanced analytics technologies. For organizations investing in digital transformation, proactively managing asset performance should be a critical component of the strategy; Industry 4.0 revolves around innovations for operational excellence, which cannot be achieved without a proactive strategy towards managing assets.
However, merely implementing APM software will not drive operational excellence that Industry 4.0 envisages or drive the ROI that businesses strive for. Instead, the real value of asset management can be realized only when data from systems across the business are connected and correlated – from enterprise resource planning systems to quality, maintenance, inventory management, and operations systems, and including real-time data from assets. Because asset performance is affected by a gamut of parameters coming out of real-time health, operations, and enterprise systems, companies that fail to take a holistic view of asset management will all too often fail to harness its full value.
Connecting in real-time to assets and other sources, aggregating and correlating the data is by no means simple. But that is the first step in creating an asset management strategy that will deliver a complete understanding of your assets. Benefits include better worker safety and asset availability, less unplanned downtime, and improved throughput, leading to a reduction in overall costs.
Additionally, a holistic approach to asset management also reduces reliance on tribal knowledge. Since asset insights are based on data, they will augment your new workforce as your experts retire, not to mention the benefits of increased employee engagement and developing a data-driven, proactive culture.
But it is the predictive intelligence that is layered on top of the data that gets the leaders ahead of their competition. Rooted in their own data and based on models trained in that data, leaders can predict maintenance activities to postpone or prevent asset failure. Prescriptive technologies take businesses even further along in their journey of operational excellence, giving them the ability to prescribe operational changes to alter how equipment performs.
“Your data can do a lot more than what you think.”
Bring in connectivity. Put your data to work. But be quick in delivering intelligence based on the data. Always integrate the intelligence gains into your process flows. While data is fundamental, integrated intelligence vastly increases your ROI. Do not fuss about accuracy, scalability, or performance. Get started. Deliver value and improve continuously. Because asset management as you know it is changing. Intelligent asset management is where the puck is going.
April 2, 2021
This glass manufacturer has been using reports and analysis techniques for the last 10 years to understand its production data. They have been using a variety of data aggregation and statistical analysis tools for self-service analytics, building their own “screens” using their home-grown and vendor-supplied tools, and finally, rolling out these tools to their 4 locations globally.
The manufacturer has an advanced data analysis infrastructure, which supports both mobile and desktop to enable easy access from anywhere. They typically monitor around 800 to 1000 data points in their lines across several processes. The current process looks like this:
- Aggregate data from OPC servers and data historians.
- Based on this data, process experts work with a set of tools to monitor the processes to make sure they are working optimally.
- A separate team of data experts uses this data to visualize, create and share reports and dashboards.
- At several points during this process, the data engineers transfer parts of the data to a cloud-based advanced analytics system for deeper analytics.
- If one location built a set of asset monitoring tools to send notifications based on asset conditions, they would then share the tools across locations. This “rollout” happens once in 6 months.
At a recent virtual event, the manufacturer learned about Makoro™ and how they can potentially move away from rolling out tools to rolling out recommendations to their plant locations. Recommendations are giving them new ideas for improving their production operations. Moving away from making data and tools available to rolling out recommendations give them a faster return on investment as they can see the improvements each quarter, and they can spot the potential for further improvement.
With Makoro, they are gradually phasing out reports and dashboards as recommendations and insights are available in almost real-time. Most of the ad-hoc analysis and manual pushing data on demand to the cloud is being taken away as Makoro™ automates the analytics on the cloud and edge as required. Makoro™ makes the rollout process redundant as each location has access to recommendations based on their data, syncing up learning from these recommendations once each month. Lack of manual intervention in Makoro™ will allow them to monitor 500 additional data points on each of the main lines, and also extend monitoring to other auxiliary processes.
With the adoption of Makoro™, they are putting their data historians and OPC infrastructure on the back end of Makoro™ connectivity. They are able to leverage all the data they have been gathering over the last several years, but instead of using the suite of analysis tools, they are letting Makoro™ do all the heavy lifting in terms of analysis, analytics automation, and visualization.
The end goal is to use Makoro™’s predictive recommendations to eliminate unplanned downtime and production outage completely.