News & Updates
May 6, 2021
Predictive analytics technologies are being used to revolutionize manufacturing operations across all sectors. Not only manufacturers but these technologies are also being used by Asset Owners to derive values based on their data instead of relying on specific OEM’s to deliver “proprietary” value. Throughout the pandemic, these technologies have also been assisting Asset Operators in managing the lifecycle of critical assets distributed across several geographic locations.
Historically, assets of various types – from those on factory floors to those in the field – have exclusively relied on calendar-based management. This meant that decisions were taken, work orders were scheduled, and pieces were ordered simply because a calendar said it was time, rather than because they were actively managed to provide value.
Reactive asset management is costing businesses millions of dollars. The magnitude of the actual impact is even unknown to most asset owners and operators.
The other issue is the siloed focus on maximizing the throughput of an asset, rather than a focus on building end-to-end intelligent operations that cut across different OEMs.
Predictive and prescriptive analytics technologies leverage artificial intelligence (AI) and advanced analytics to develop intelligent operations. These technologies allow manufacturers, owners and operators to predict the operational impact to an asset, the line, the floor or to a location. Here is how Makoro™ leverages predictive and prescriptive technologies in building intelligent operations.
Makoro™ Edges connect with assets and devices on the front end and communicate with Makoro™ Hub on the back end. It transmits machine and process data such as flow rate, oil and water temperatures, vibration measurements, and machine operating hours.
After that, this data is combined with data from different operations and business sources. This is accomplished through Makoro™ Bind, the connector’s interface. After that, it is analysed using a combination of market rules and Makoro™ Mind’s predictive, Al-powered algorithms. While Makoro™ predicts a possible issue, it also does a root cause analysis of the issue. Further, it proactively generates maintenance requests, schedules and assigns the requests, and makes duration, fix and parts recommendations. As data flows through the Hub, Makoro™’s continuous intelligence delivers “unexpected” predictions, insights and recommendations.
Makoro™ learns and evolves as customers engage with the recommendations. And gradually establishing a “golden” operations workflow in which asset management actions are data-driven, traceable, and have been validated by the customer’s workforce.
Through deep-domain artificial intelligence, Makoro™ delivers a rapid time-to-value for customers. It results in higher asset uptime, lower cost of operations, lower maintenance costs and higher workforce adoption.
The ability to anticipate is the competitive advantage in the fast-paced #Industry40 adoption and Makoro™’s #PredictiveRecommendations give you that edge.
MakoroTM’s dynamic learning framework brings operations management to the next level, allowing sets of validated guidelines with extremely high validity and trust scores to be repeated across several locations to maximise value. So instead of sharing data as reports and dashboards, they share recommendations/prescriptions.
Makoro™’s Recommendations Dashboard tracks asset performance metrics and correlates them to recommendations. Leaders who have embraced Makoro™ have achieved more than 11% improvement in their operations agility.
To get started with Makoro™, sign up for our 10-Day Outcome Challenge.
April 26, 2021
Modernization has become more than just a buzzword in manufacturing; it’s a survival tool for established original equipment manufacturers (OEMs) In the era of born-in-the-cloud competition, innovative technologies like the industrial internet of things, artificial intelligence and cyber-physical systems accelerate manufacturing, enable hyper-demand economics, and reduce inefficiencies in the manufacturing floor.
Parts procurement, inventory management, ordering and shipping, customer account management, and product lifecycle services all play a significant role in brand reputation and customer satisfaction.
The ability to anticipate is a competitive advantage.
Partnering with a leader in product and customer lifecycle experience enables OEMs to focus on what comes next. A partner with a deep-domain understanding of the manufacturing supply chain coupled with a leadership position in predictive technologies can not only assume complete lifecycle improvement and customer lifecycle support operations but also provide a path to better manage your supply chain risks through predictive insights. This helps your business build intelligence in your operations so you are more aware and are better prepared to turn the right levers in your business transformation.
Striking the right partnership is key to any digital transformation. With the right partner, you can concentrate on new strategies and drive innovation while your partner takes care of product installation, migrations, ongoing maintenance, certified repair and refurbishment, through a channel-agnostic, pay-as-you-go delivery model.
Continuous value demonstration is key. The right partner will demonstrate the incremental value of your digital transformation initiatives and continuously improve upon the intelligence in your operations so you can achieve your e-cycling and sustainability goals.
CodeData is here to help you capitalize on new ideas and fresh perspectives so you can start rethinking your current challenges, plan to achieve your modernization goals, and come out on top as a leader of the next industrial revolution.
Schedule a demo to see how we can inspire you.
April 24, 2021
Introduction to Makoro™ AI – how Makoro™ derives its name from the Bantu language and the foundational principles of Makoro™. The proliferation of connected assets makes it impossible to manage assets by viewing data, reports, and dashboards. Makoro™ manages assets through natural language recommendations, which operators, process engineers, and maintenance engineers can act upon without having to depend on data scientists.
Makoro™ illustrates the power of #AppliedArtificialIntelligence in solving transformative problems in the manufacturing supply chain.
#MakoroAI #CodeDataIO #PredictiveRecommendations #NaturalLanguageRecommendations #PredictiveAssetManagement #ContinuousIntelligence
April 23, 2021
The transformation from linear plant setups to dynamic and interconnected systems is one of the greatest challenges for manufacturing today.
The Industrial Internet of Things (IIoT) is accelerating the pace of change around connecting machines, yet less than 30% of manufacturers have extensively adopted Industry 4.0 technologies.
Unfortunately, current asset management tools do not recommend solutions, they simply show views of data from assets, maintenance, and operations.
And that data is not enough to drive asset performance.
You need to look beyond data so you can deliver a faster value for your business.
Makoro™ takes asset performance beyond data, reports, and dashboards. It correlates and analyzes data from machines, and enterprise, and operations systems and recommends solutions to improve asset performance and lower maintenance costs, and drive workforce adoption.
See what Makoro™ can do for your business – schedule a demo.
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.