News & Updates
September 21, 2021
To assist the rapidly increasing e-mobility sector, as well as the energy transition, climate change, and sustainability, all of these initiatives require novel solutions. Additionally, alternative propulsion concepts must be developed to considerably cut CO2 emissions.
That is why advancements in battery manufacture are becoming increasingly important.
However, which batteries and production techniques are capable of meeting escalating demand and stringent specifications? How can manufacturers maximize the sustainability, efficiency, and quality of their plants while automating their processes? New comprehensive automation concepts, such as those based on artificial intelligence and robotics, are critical. Additionally, these notions should consider market requirements, as well as the demands of policymakers and the battery industry. Thus, what are the current trends and future approaches in battery manufacturing that will enable European companies to seize the lead in energy storage for electric vehicles?
Battery makers must excel in terms of quality, increased efficiency, and resource optimization in order to compete better. As the field of e-mobility advances, more advanced battery technologies are being developed. It ensures the vehicles’ durability, safety, and operation. Lithium-ion pouch batteries suit a number of critical current industrial and automobile manufacturing needs. However, pouch cell manufacturing is more complex and time-consuming than cylindrical battery manufacturing. This, in turn, puts unique demands on manufacturing processes. Manufacturers are looking to artificial intelligence to assist with their manufacturing processes. For instance, AI can assist in optimizing machine efficiency and ensuring defect-free output.
Combining artificial intelligence, sensing, control, and robotics delivers higher quality.
While battery producers must react to the market’s ongoing evolution, they demand production processes that can be altered more quickly and flexibly than ever before to suit changing requirements. Combining artificial intelligence, sensing, control, safety, and robotics into a single automation platform enables manufacturers to meet customer criteria for product quality and predictive maintenance while also reaching critical sustainability goals.
Additionally, assistance with integrated battery cell inspection solutions, as well as solutions for electrode and battery module manufacture, can assist in streamlining the testing and providing end-to-end traceability throughout the battery cell’s life.
The technology ensures sustainability.
Battery manufacturers and suppliers require a dependable partner that can give theAsset Performance Managementm powerful technology and relevant advice from a single source in order to be inventive, adaptable, and future-oriented. A holistic, artificial intelligence-based solution can assist industries in reducing waste. When used in conjunction with an intelligent warehouse system and mobile robotics, firms can significantly increase process efficiency and productivity.
Simultaneously, battery cell quality – including capacity and battery life – should be covered sustainably by a manufacturing and lifecycle control solution that is backed up by an in-line inspection system. This solution must take into account all stages, from manufacture to usage and recycling. By applying these technologies, businesses take a critical step toward the future of sustainable industrial and battery production.
Recommendations based on data maximize utilization of production resources.
Today’s batteries as well as their production generate massive amounts of data. Makoro™ provides a range of device and enterprise system connectivity protocol options, and a recommendation system powered by digital performance twin, enabling manufacturers to translate the data generated by the manufacturing processes into a wealth of real-time recommendations. Leveraging these recommendations in battery production helps manufacturers improve their productS and production systems efficiently. They are able to create new business opportunities based on recommendations based on aggregated, correlated, and analyzed operational data.
As a result, battery manufacturers achieve::
- Improved productivity of existing plants
- Reduced inventory and throughput time
- Maximum utilization of production resources
Research indicates that proactive asset recommendations result in an 11% – 13% reduction in raw material usage and a potential savings of up to 15% – 18% in energy utilization.
August 17, 2021
Digital twin refers to the exact virtual prototype of an object, process, or system covering its entire life cycle. This prototype is based on real-time data and uses simulation, machine learning, and reasoning to help decision-making.
Digital twins form a bridge between the physical and digital worlds.
The concept of the digital twin was first used by NASA. With the development of the Internet of Things (IoT), the usage of digital twins is expanding. With the onset of Industry 4.0, the digital twin is becoming inevitable to be used by businesses of all scales to optimize and increase profits of their operations. By allowing the creation of digital copies of real-time objects digital twins have opened new avenues of production, maintenance, design, research, and innovation.
Digital twin allows designing, and real-life simulation of an entity even before it is created. This enables the production of only those products that match the standards defined. For instance, with digital twins, 10 different car models can be digitally created, and with real-life simulation can be digitally checked for possible shortcomings, and based on this a near-perfect product can be created.
Similarly, with digital twins, it is easier to test products in different scenarios without physically requiring the test scenarios. It helps in the optimization and customization of products. In the automobile industry, a digital twin of a car can be tested to handle different collision scenarios, and accordingly, the safety procedure of the car can be updated.
Digital twins in combination with the Internet of things allows for real-time monitoring of objects. With the usage of sensors, the digital twin is continuously monitored remotely. This enables early diagnosis of any future breakdown of the object or system.
Digital twin equipped with real-time data is a tool without rivals in making predictions about possible breakdowns, future wear, and tear. This enables businesses to undertake more efficient preventive maintenance. This reduces the downtime of any unit. With a digital twin, it is also possible to identify the part most likely to malfunction and possible routes to fix the problem.
Teleoperations is one of the key advantage areas of the digital twin. Through teleoperation, it is possible to control the physical object, system, or process remotely. It allows controlling physical objects virtually, virtual objects physically and virtual objects virtually. The combination of these possibilities helps in creating a teleoperation ecosystem. It is of indispensable value in controlling operations in hazardous industries and the environment.
As businesses adopt digital operations and industry 4.0, the firms employing this technology are already gaining an edge in the market. Digital twins are enabling them to better predict, design, maintain and operate their products. The availability of increasingly accurate models and predictions gives them an edge over those that have not adopted the norms yet.
INDUSTRIES EMPLOYING DIGITAL TWIN
POWER GENERATION- Power generation industries employ humongous machinery and operation designs. Digital twin not only helps in better design and modification but also in time maintenance. This sector cannot face shut down as it provides power to all other sectors. Digital twins help in checking any possible fault well in time.
LARGE PHYSICAL STRUCTURES AND THEIR SYSTEMS- Digital twins are imperative in designing large physical structures such as bridges and offshore drilling operations. At the same time, the digital twin is used in the maintenance and remote operations of systems within these structures. For instance, in the case of oil drilling, it helps to predict the depth and exact location of drilling operations most viable for the equipment.
MANUFACTURING OPERATIONS- The manufacturing operations are increasingly using digital twin at all levels. Ffom product design, customization, process, maintenance to delivery of the product.
HEALTHCARE SERVICES- Just like with physical objects, a digital twin of a human can be created. In the healthcare system, the digital twin is used to make a prognosis of the patient, try the possible treatments, check their consequences. It is being used to develop better medical facilities.
AUTOMOBILE INDUSTRY– The automobile industry operates in complex interwoven systems. The digital twin helps in the design, simulation, and prediction of the automobile as well as that of the environment surrounding it.
These industries are the most prominent employers of digital twins but by no means the only users of digital twins.
DIGITAL TWINS AND BUSINESS FUTURE
- Up to 89% of all IoT Platforms will contain some form of Digital Twinning capability by 2025
- Digital twinning will become standard feature/functionality for IoT Application Enablement by 2027
How can Makoro™ assist?
Makoro™ employs a cloud-agnostic approach that fully leverages the customer’s infrastructure and installs on the edge, in public/private/hybrid cloud, and in the customer’s data centers to expedite deployment. Makoro™ is also available as a fully managed application suite on Makoro™ Cloud.
Makoro™ Predictive Asset Performance Management solution collects and correlates data from the manufacturer’s internal applications, inventory management systems, and maintenance management systems in real-time and generates recommendations for optimizing asset and workforce utilization while reducing overall maintenance costs. The digital performance twin in Makoro™ Mind constructs an asset health and performance model from data from linked devices and maintains it through periodic re-training. As a consequence of real-time IoT data from the asset, engineers have a full picture of how the asset is operating. Makoro™’s Performance Twin enables the identification of possible asset issues, remote troubleshooting, and integration with Makoro™’s Recommendation System to offer contextual suggestions for proactive asset performance improvement.
And, because Makoro™ enables secure access to your plant’s predictions, insights, and recommendations from any device, it plays a critical role in your remote operations strategy, enabling your operations executives to make more informed, timely, and consistent decisions about their plant’s operations remotely.
Request a demonstration to discover what Makoro™ can do for your business.
August 9, 2021
Recommendations from Makoro™ deliver improved asset and process performance consistently. But instead of looking at data and making decisions yourself, the system provides a simple prescription of actions to be taken based on deep analytics. This improves consistency in decision-making and ensures compliance.
Decision-making is transparent as all actions on recommendations are tracked by the system and learned from to make future recommendations better.
Makoro™ connects to any source of data, including data from log files, and excel spreadsheets, and the data that has been sitting on your flash drives.
Makoro™ offers simple SaaS pricing (per asset per month per user) for customers – asset, equipment, and process manufacturers, owners, and operators.
Makoro™ operates frictionlessly across Edge, Private, Public, and Hybrid Clouds, and Customer Data Centers, so it leverages customer’s infrastructure to the maximum.
Makoro™ now offers 4 capability levels – starting with Starter, through Intermediate, Advanced, and Pro, so customers can onboard and scale with ease depending on their requirements.
The 10-Day Challenge program is the right point to start and mitigate your risks in Makoro™ adoption.
May 11, 2021
Industry 4.0 is characterized by a connected world. But Covid was a rude awakening – when manufacturers and asset owners/operators discovered the truth about their not-so-nimble operations and not-so-connected supply networks,
Covid intensified market developments that were already underway, although hesitantly.
Globally, we are now seeing a more intense focus on “connected” supply chains. Manufacturers have expanded on the idea of just-in-time production and are now more flexible in their adoption of “agility” in order to respond to market fluctuations, trade policy adjustments, and natural disasters.
Covid has forced manufacturers to reconsider their rigid operations. How do I strengthen the resilience of my supply chain? How will I manage a changing workforce? How do I make the transition from a workforce in which 80 to 90% of employees report to work daily to one that allows for remote work? These are the hard questions manufacturers are challenged with.
Additionally, there is a demographic change in ageing employees and the arrival of a new generation of workers, and manufacturers are attempting to retain the tribal knowledge before it is too late.
Moreover, they are attempting to attract and retain talent by transitioning from analog to digital manufacturing.
What function do artificial intelligence and advanced analytics play in all of this?
Around 15 years ago, the industry asked, “How do we extract more market value from what we’re doing?” Data and networking were instrumental in this initiative. We needed to tie everything together in order to extract the data.
Now we have an abundance of data that we frequently don’t know what to do with, resulting in data paralysis. More than 75-80% of the data that is stashed away is never analyzed.
That is where an artificial intelligence-enabled solution such as Makoro™ comes in.
Manufacturers use Makoro™ to derive insights and recommendations to improve the performance of its products across multiple geographic locations and to fuel newer, servitization-based business models. Owners and operators use Makoro™ to derive predictions, insights. These recommendations are necessary to build intelligent operations and/or manage asset fleets more efficiently.
With Makoro™, recommendations and insights automatically reach the intended workforce personas based on their role and job responsibilities, and become actionable immediately, without the need for data scientists to interpret the results.
This is transformative – data does not travel, and reports and dashboards do not need to be shared. Recommendations/prescriptions travel and automatically become part of your “golden” playbook to build intelligent operations.
Makoro™ builds on Industry 4.0’s networking and data while focusing on augmenting the experience for the Workforce of Tomorrow (WoT). Thereby extending the definition of Industry 4.0 to the workforce and the environment.
Makoro™’s always-on, secure and scalable asset performance solution powered by #AppliedArtificialIntelligence and #PredictiveRecommendations gives you the edge in the fast-paced #Industry40 and drives frontline adoption.
Sign up for the Makoro™ 10-Day Outcome Challenge and see the results yourself.
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.