News & Updates
May 7, 2021
. According to PwC, computers would drive 70% global GDP growth between now and 2030. This represents a nearly $7 trillion dollar contribution to the United States’ Gross Domestic Product (GDP) from the combined development of artificial intelligence, machine learning, robotics, and embedded devices. This is the beginning of the emergence of a modern machine economy.
For those unfamiliar with the computer economy, it is a system in which intelligent, wired, autonomous, and economically self-sufficient machines or devices perform required manufacturing, distribution, and operations activities with augmented human involvement. The growth of this economy is critical to the rise of Industry 4.0.
Visionary leaders can integrate new technology and capital investments in ways that enable their businesses to develop, expand, diversify, and ultimately improve lives. This change will help in enabling the global adoption of new economic models. But this will not happen overnight or can be designed & implemented by itself. In order to provide impetus we need to:
1. Encourage participation in manufacturing:
While the majority of people agree that manufacturing is critical to our economy, they do not recommend it to their children. Between now and 2028, it is estimated that 4.6 million manufacturing jobs will go unfilled. The workforce is rapidly losing its second-largest age group, and millennials (the largest generation) have historically been uninterested in manufacturing employment. Other than that, they are often attracted to fields such as technology, engineering, and finance. The underlying problem may be one of understanding, as manufacturing in the future would require a much higher level of technology, engineering, and finance to work properly.
2. Nurture diverse abilities:
The manufacturing workforce is undergoing change. The number of solely manual, repetitive tasks is decreasing as technology progresses to automate and robotize these tasks. 50% of manufacturers have now implemented some level of automation, and they now need individuals with analytical thinking, programming, and digital skills. The occupations of the future will include titles including Digital Twin Engineer, Robot Teaming Coordinator, Drone Data Coordinator, Smart Scheduler, Factory Manager, and Safety Supervisor, among others.
3. Invest in both people and technologies:
While unskilled positions can be filled reasonably quickly, it usually takes months to fill a skilled role, and even longer for a person to learn the necessary skills before applying them on the job. Meanwhile, there is increased pressure to maximize the use of time and expertise of the current workforce, which may result in burnout. To prosper in the computer economy, we must make substantial investments in both people and infrastructure. Concentrating exclusively on infrastructure will generate short- and possibly medium-term gains. But it is not sustainable in the long run, and everyone loses.
4. Train and re-train
When individuals are inspired and have access to something to learn, the human capacity for learning is almost unlimited. We must ensure that enough training is available to workers at all levels of the organization. This will ensure that new hires are quickly brought up to speed.
Employers, like employees, must rethink and develop new skills – they must develop new methods for cultivating and retaining talent.
Makoro™’s #DynamicLearning technologies help you recruit and train seasoned staff, and it augments new employees as they enter the field.
Schedule a demo of Makoro™ today to find out how your workforce can leverage its augmentation capabilities.
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 30, 2021
The evolution of enterprise asset management is what makes newer business models possible. The real-time analytics and predictive maintenance allow asset manufacturers to develop entirely new business models, according to a report by the International Association of Manufacturers (IAM).
According to the IAM study, 70% of businesses are looking for new ways to generate additional revenue from their properties, with the majority citing the new business model as an appealing option.
Manufacturers are increasingly exploring asset-as-a-service business models to offer business outcomes rather than only physical assets. As a result, the responsibility for ensuring asset uptime shifts from the end-user to the manufacturer. With the manufacturer now being in charge of asset management and servicing, thereby creating more opportunities for cooperation with the customer.
Additionally, the study discovered that 50% of those surveyed were searching for ways to cut down on maintenance visits to their facilities.
While the complete realization of the asset-as-a-service economy is still evolving. The leaders are already adopting technologies and processes that will enable them to deliver asset uptime profitably. Clearly, the success of this model depends on how effectively manufacturers can shift to a more predictive state.
From predicting asset failures to predictive maintenance, Makoro™ enables businesses to identify problems before they occur. Makoro™ lets manufacturers connect to assets in the field and deliver real-time predictive recommendations. Which in turn allows them to reduce maintenance costs and deliver consistent asset uptime.
Schedule a demo to learn how Makoro™ can help you adopt new business models.
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 27, 2021
The term “Industry 4.0” is often used interchangeably with “Smart Manufacturing.” Despite widespread public confusion and initial business reservations about Industry 4.0, the benefits appear to be very promising. It is expected that over the next five years, an AI system will be able to run computers autonomously.
Additionally, AI benefits businesses by improving operating efficiency. It can further shorten time to market and reduce factory safety incidents. By connecting business data end-to-end, from supply chains to manufacturing, delivery, and use, AI will alert employees to both possible challenges and opportunities.
The first step in Implementing Smart Manufacturing in real scenarios is to collect data from a variety of structured and unstructured sources. It could be from IoT and IIoT systems, HMIs, PLCs, ERP, and CRM systems, as well as manual data records. Integrating data on raw materials, processing, manufacturing, shipping, distribution, and transportation all the way down to the customer level adds increasing value across the entire manufacturing supply chain.
But data collection and aggregation is the first step. The real value is realized by what businesses do with the data. Some go down the path of data visualization to understand data better. But advanced AI systems like #MakoroAI aggregate, correlate, and analyze this data in order to make recommendations that directly impact business outcomes and drive workforce adoption.
Makoro™’s always-on, secure and scalable asset performance solution. It is powered by #AppliedArtificialIntelligence and #PredictiveRecommendations gives you the edge in the fast paced #Industry40. Thereby reducing the downtime and maintenance costs.
Sign up for the Makoro™ 10-Day Outcome Challenge and see the results yourself.
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.