News & Updates
Predictive Asset Management
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 29, 2021
Manufacturers are looking to digitize their activities to meet the demands of the pandemic. The aim is to create a single operating mechanism that spans all available resources on a global scale.
This necessitates consistent structures and standardization, which must be facilitated by emerging technology, agile processes, and data access. It is essential to provide global insights into plant performance combined with business background from enterprise systems.
The greater the amount and the variety of data that learning systems can ingest, the more accurate they become. Digital processes and the capacity to process vast amounts of data are essential components of digital transformation.
A key element of adoption for digital transformation initiatives is value demonstration.
A large percentage of pilots rot in the “Pilot Purgatory” because they do not demonstrate a clear business value. Makoro™’s dashboard provides a continuous value demonstration of recommendations on specific business outcomes related to assets, maintenance, and workforce. These are quantified values that also act as incentives to continuous asset and process improvement.
Another impediment is workforce adoption.
Deployment of new tools often is too technology-focused. It does not put business capabilities in the hands of the existing operations workforce, the real catalysts who leverage their domain and process knowledge to derive value from these tools. Makoro™ is created for the operations workforce – for operators, maintenance engineers, floor managers, and operations executives. Makoro™ gives recommendations that are seamlessly integrated into their regular task workflows, making them easy to adopt.
We internally say that “Makoro™ solves the issues on the production line that keeps operators up at 8 o’clock on a Friday evening.” Do you really want to call the data scientists at that time to interpret data and drive decision-making? That’s where the natural language recommendations really make their mark.
A third barrier is the high cost of a scalable solution.
It is one thing to experiment with analytics – ingest data from a few machines, run experimental algorithms, and derive value (which is also a necessary step in the lifecycle) but building a scalable solution that works for thousands of assets and hundreds of devices per asset, and supports hundreds of workers across multiple locations needs well-thought-out vision, risk mitigation strategies, and investment plans. Makoro™’s Automated Operations and Continuous Intelligence scales up and down in a frictionless manner across devices, edges, and hybrid clouds to deliver the scalability that businesses need.
We should aim higher, but implementations must start smaller in scale, with an eye on delivering maximum impact. The rollout should be line-by-line and site-by-site, which mitigates risk and delivers value at each stage.
Want to know how Makoro™ can drive adoption, scale, and value in your business? Sign up for a demo.
April 28, 2021
During these times of social and economic distance, the incorporation of Artificial Intelligence into conventional manufacturing, supply chain, and quality management is already proving to be a game-changer across verticals.
AI is not only the trigger, but it is also the wheels. One of the growth drivers in manufacturing, with growing competition and declining margins, is to reduce downtime and improve asset efficiency. However, current asset performance management products and solutions are flawed. As they only offer data views in many shapes and forms without actually recommending solutions.
As a result, asset management is costly, arbitrary, unreliable, and inefficient.
When it comes to managing asset performance, more than 78 percent of our customers tell us that data alone is insufficient. And as the volume and complexity of data increases, it is impossible to dig through data to make the best decisions. There is no transparency in the decision-making process. There is also no validation in terms of acceptance of the decision and its impact on the business outcomes.
Makoro™’s innovative fusion of digital performance twin, artificial intelligence, and recommendations engine extends asset performance beyond reports and dashboards. It delivers real-time recommendations that demonstrate value to business continuously.
Makoro™’s always-on, stable, and scalable asset performance solution is driven by #AppliedArtificialIntelligence and #PredictiveRecommendations. It gives you a competitive advantage in the fast-paced #Industry40 while lowering downtime and maintenance costs.
Schedule a demo to see how we do it.
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 19, 2021
Makoro™ uses applied artificial intelligence to solve transformational problems in the manufacturing supply chain.
Makoro™ AI differentiates itself in Enterprise Asset Management and Asset Performance Management spaces through its AI-powered predictive asset performance management for asset manufacturers, owners, and operators. Makoro™ AI lets you connect to all operations and IT data sources and transforms data to recommendations in minutes – recommendations that power higher asset uptime, lower maintenance costs, and higher workforce engagement.
Makoro™ illustrates the power of #ArtificialIntelligence applied to solve the deep-domain problems of the manufacturing supply chain.
#MakoroAI #CodeDataIO #PredictiveRecommendations #NaturalLanguageRecommendations #PredictiveAssetManagement #ContinuousIntelligence
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.