News & Updates
June 18, 2021
The #IndustrialManufacturing world is poised to learn (and benefit) from the massive digital pivot that their B2C counterparts are already benefitting from.
Industrial companies must learn from the B2C experiences and pivot into digital. They must adopt digital through the entire #SupplyChains to get back the operational cost advantages.
A recent McKinsey & Company survey showed that two-thirds of business-to-business (B2B) customers prefer remote human assistance or digital self-service when making purchases.
Per Gartner, 36% of heavy manufacturing CIOs reported that digital disruption caused operating cost competitiveness to fall behind their digitally advanced competitors.
Recommendations (customer, product, etc.) have delivered consistently higher customer engagements and driven massive growth at #retailers. #MakoroAI delivers the benefits of recommendations powered by #DigitalTwins to asset manufacturers, owners, and operators.
With the exploding volume, format, and velocity of data from sensors, enterprise, and operational systems, #DataIsNotEnough to make fast, transparent, and consistent decisions. #AssetPerformanceRecommendations from Makoro™ is the future for medical, #industrial, and #manufacturing processes.
Take a read below.
June 17, 2021
The global manufacturing industry is amidst a massive transformation that encompasses the entire supply chain. The previous industrial revolution was a giant step in modernizing the industry, but the impact of Industry 4.0 is seen to be much larger. It is the process whereby the automated industry of Industry 3.0 is geared towards digitization and creating smart industries. It entails the usage of connected assets, IIoT, Digital Twins, Data, Artificial Intelligence, and Advanced Analytics to improve the efficiency, transparency, and consistency of the overall supply chain.
How is Industry 4.0 relevant for India?
- Bridge the Gap between Supply and Demand: The population of India is on an upward growth curve and so is the consumption rate, which tends to rise further each day, thereby putting tremendous demand pressure on the manufacturing industries. At the same time, this increases the gap between demand and production capacity. To bridge this increasing gap and increase productivity, manufacturing in India must adopt newer technologies. Productivity gaps identified by analysis of comprehensive and real-time data from production processes are the first step towards understanding the current state of the systems. This can be further improved through the adoption of predictive and prescriptive technologies.
- Eliminate Waste: Industry 4.0 uses real-time data and artificial intelligence to improve production operations. The real-time data provides updated information about the functioning of the machinery. It helps in optimizing the timing for the purchase and storage of raw materials, thereby eliminating wastage. It also helps in identifying malfunctioning machinery and gives timely information for their maintenance, preventing high wear and tear, and ensuring the best utilization of raw materials. Industry 4.0 is a multi-pronged approach for waste elimination and sustainable production.
- Improve Quality: Before the fourth industrial revolution, the quality check was aimed at maintaining the flaws in the products limited below a certain threshold. The process itself was heavily reliant on the quality check personnel. The data available, even though abundant, was not put to use and stored away for later analysis, which was never performed. But with Industry 4.0, the real-time data provides the exact checkpoints for products, improving quality continuously.
- Enhance Customer Satisfaction: India is a diverse nation. As a result, products have significant variations due to consumer preferences. Multiple factors such as culture, age, language give rise to ever-changing and evolving consumer preferences in the same time-space. This poses a challenge to manufacturers to produce personalized products. Demand for personalized products is growing – and appears to stick on. We all seem to want products personalized and right-sized to fit our preferences, personalities, and lifestyles. This is a trend that OEMs can’t afford to ignore. Manufacturers must implement strategies to meet this new demand for customization. Industry 4.0 technologies lead in the direction of agile, small-batch, personalized manufacturing, to deliver products customized to specific consumer personalization requirements, thereby enhancing customer satisfaction.
- Increase collaboration among manufacturers, startups, and research institutions: Industry 4.0 relies heavily on the knowledge workforce. Its success is driven by active collaboration among manufacturers, researchers, and startups. India, with its technology boom and the startup ecosystem, already has a skilled workforce to cater to the needs of innovation in the manufacturing supply chain. At the same time, there is also plenty of active research in technologies like Computer Vision, Artificial Intelligence, Process Optimization, and such. Bringing together startup innovation and advanced research can deliver immense value to the adoption of Industry 4.0 in the manufacturing supply chain in the country. This collaboration will also diversify the economic base of the nation.
- How can Makoro™ help?
MakoroTM drives process optimization in the manufacturing supply chain by delivering continuous intelligence through Makoro™ Mind, the data-driven core which leverages IoT, Digital Twin, AI, and advanced analytics to recommend solutions that make assets perform better.
Moreover, Makoro™ leverages customer’s existing infrastructure (without any bias for Edge, Cloud, or On-Premise). It deploys seamlessly across customer’s existing private/public/hybrid cloud, on-premise, and edge systems.
The Recommendations Dashboard demonstrates the continuous value of Makoro™ to customer’s processes, correlating asset, maintenance, and workforce metrics in real-time with sentiment, acceptance, confidence, and relevance of recommendations.
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June 7, 2021
Globally, the market for connected worker solutions is predicted to expand at a high pace, owing to growing concerns about employee safety and increased throughput. Connected worker solutions are used in a wide variety of industry verticals, with manufacturing serving as a specialization.
Digitalization, productivity enhancement, and industry 4.0 have all been vital growth indicators.
The digitalization of the supply chain and the integration of connected worker solutions within the plant are ensuring the market’s potential growth. IIoT (Industrial Internet of Things) deployment for the purpose of enhancing plant productivity and ensuring employee well-being is expected to fuel market expansion over the forecast period.
The global market for connected worker solutions is expected to expand at a CAGR of around 23% between 2020 and 2030.
What Are the Advantages of Using Smart Wearables in Manufacturing?
Smart wearables consist of intelligent headgear that delivers intelligent solutions, such as determining when to replace the helmet and its state of repair. Additionally, smart glasses that enhance visibility and enable real-time troubleshooting are just a few of the advantages of smart wearables over conventional ones.
For example, the healthcare industry makes extensive use of wearables such as the Fit Bit to record and track patients’ chronic diseases, alerting both the patient and caregiver to concerning trends.
Similarly, CBT’s wearable computing headset can be worn with conventional headgear such as a ball cap or a basic headband. This device is intelligent due to its IoT capabilities; it does not have any extra attachments. Additionally, this device responds to basic voice instructions, making it more user-friendly. These elements contribute significantly to the enormous benefits of smart wearables in connected workforce solutions.
What Role Do Connected Worker Solutions Play in the Evolution of Smart Manufacturing Practices?
The implementation of computer-integrated manufacturing with rapid design modifications and higher adaptability, as well as the digitalization of the manufacturing process with more agile personnel training, constitutes smart manufacturing practice. To summarise, the smart manufacturing environment is comprised of automation, real-time monitoring, and networked, and real-time data & analytics.
These manufacturing methods lay the groundwork for the integration of connected worker solutions into industrial processes. Industrial activities benefit from connected worker solutions that provide a consistent experience of competency and floor management in real-time, leveraging critical statistical data from business software.
Smart manufacturing methods are already being implemented in a variety of industries, and the combination of smart manufacturing practices and connected worker solutions is positioned to generate significant growth potential for the market in the future years.
What Impact Will IT/OT Convergence Have on Demand for Connected Worker Solutions?
IT is an acronym for information technology, while OT is an acronym for operational technology. The next section discusses how the convergence of these two technologies would affect demand for connected worker solutions.
The integration of manufacturing processes, regulating processes, and physical occurrences with back-end software and hardware for processing and evaluating the acquired data is referred to as IT/OT convergence. Due to widespread wireless Internet connectivity, the convergence point between these two technologies has gotten very near over the years. Convergence of IT and operations technology creates an enormous opportunity for manufacturing processes by combining IT capabilities with operational technology components and by structuring direct machine-to-machine learning with centralized servers, which has altered the overall dynamics of manufacturing processes.
Convergence has now created value for connected worker solutions that provide unmatched real-time visibility and a complete understanding of production processes, affecting the overall market. As a result of enhanced convergence, connected worker solutions are expected to grow at an exponential rate during the projection period.
What Impact Will Efficient IIoT Deployment Have on Connected Worker Solutions?
The Industrial Internet of Things is accelerating the adoption of modern technology in manufacturing processes. The Industrial Internet of Things is wreaking havoc throughout manufacturing industries and changing current industrial processes. This, in turn, is certain to restructure nearly every area of manufacturing, from the way items are researched, planned, fabricated, produced, disseminated, and consumed to the way manufacturing supply chains, and factory floors operate.
The IIoT enables the convergence of IT and OT, which is a critical part of connected worker solutions. Consumers have long desired this implementation, which enables the user to leverage an IIoT platform to accumulate massive data via machine-worker interactions. This mobilization aids in the prevention of safety issues by predictive analytics, ultimately increasing staff productivity and safety.
Additionally, IIoT provides consumers with intelligent computing. Cognitive computing is the process of using computer models to simulate human thought processes in puzzling situations characterized by ambiguous and tentative responses. North Star Bluescope has teamed with IBM to develop a cognitive computing platform that integrates with IBM’s Watson Internet of Things platform to assist personnel in dangerous areas where their lives may be at risk.
Applicability of Connected Worker Solutions
The United States has a history of early technological acceptance and utilization, including digitalization of supply chains and mobilization of advanced technologies such as 5G and electric car infrastructure.
The extensive use of connected worker solutions in the automotive and oil & gas industries has been the primary driver of the market’s clear expansion in the country. Additionally, with a majority of firms such as Honeywell, Oracle, and Intel headquartered in the United States, the implementation of connected worker solutions across a variety of industrial applications is positioned to create enormous opportunities in the short-medium term.
Effects on a variety of industries
Mobile devices/tabs are configured to expand most of the hardware. This expansion is aided by the simplicity with which mobile devices can be used and their compatibility.
Mobile devices and tablets are also likely to see an increase in popularity as a result of BYOD (bring your own device) usage. Additionally, mobile devices assist in supplying an employee with up-to-date analytics, ensuring the employee’s safety.
The oil and gas business is undergoing transformational changes on a scale never seen before. With uncertainties over industrial output and opposition from environmentalists, the market faces significant headwinds. However, the oil and gas business has a greater adoption of connected worker solutions.
This industry requires workers to evaluate and harness available data in order to make timely and correct important judgments. These characteristics contribute to the efficient and comprehensive adoption of connected worker solutions.
Connected worker solutions are applicable to both small and large businesses. However, there is a sizable market for huge organizations. This is because major firms have ample finances available to invest in sophisticated technologies.
Small and medium-sized businesses account for a smaller portion of the market because deploying connected worker solutions inside the industry is not cost-effective. The cost of solution deployment may burn a hole in the company’s wallet, a factor limiting widespread adoption.
Natural language recommendations from Makoro™ augment your workforce, so you can capture tribal knowledge, rapidly onboard new employees, and enable them to be productive from day one.
May 29, 2021
When manufacturing began to embrace digital technology a decade ago, it acquired a new term: smart manufacturing, or Industry 4.0. By incorporating cloud, automation, advanced analytics, machine learning, and big data into manufacturing and supply chain management operations, a connected ecosystem for manufacturing and supply chain management was created, which grew into a market that is experiencing rapid growth. In Jan’20, the sector was poised to double in size to more than $300 billion over the next five years.
Then came the pandemic. By early spring, millions of workers had been laid off. Several plants halted production temporarily or reduced output to allow workers to spread out and maintain a safe distance from one another. Investment in smart manufacturing also decreased by 16%. According to some researchers, such a pullback would dampen investment through 2025.
However, manufacturing executives and service providers indicate that investment in smart manufacturing will accelerate. It is more than $400 billion by 2025. This is because Industry 4.0 technologies improve operational efficiency, strengthen supply chains, and enable a more personalized customer experience and the potential for data-driven top-line growth.
Before COVID-19 impacted the manufacturing and delivery processes for every conceivable product, some businesses had already begun a digital transformation.
For instance, the automotive industry has already embraced new business models in order to address strategic imperatives such as connected and electric vehicles, as well as automated and shared solutions. The pandemic provided additional impetus for businesses to rethink their digital strategy, accelerate their migration to these technologies, and reduce their reliance on specific locations, thereby increasing their operational resilience.
As a result, supply chains in manufacturing have become increasingly complex and integrated. The Demand for more efficient equipment and increased manufacturing yield has increased significantly. Enterprises are now leveraging applied analytics to predict and mitigate operational disruptions within and across plants and the supply chain.
Instruments of the New Age
Businesses are increasingly using digital twins. AR & VR technologies are being used in a variety of applications, most notably for equipment maintenance and employee training in manufacturing plants. 4G, LTE, and 5G networks are being established to support low-latency communications required for machine-to-machine communication and edge computing within plants. Cybersecurity, cloud computing, and the IoT are also gaining traction.
At the same time, cybersecurity is increasingly becoming a challenge that is getting a lot of attention. We’ve already seen numerous instances of hackers attempting to penetrate manufacturing sites, such as the malware attacks that brought a pure-play semiconductor company to a halt. The number of IoT devices could triple to tenfold its current level. And each device provides a point of entry for hackers. Simultaneously, multinational manufacturers must comply with local regulations.
Smart manufacturing enables more adaptable, customized manufacturing setups, frequently utilizing additive manufacturing solutions to deliver personalized products and enhance the customer experience. At the heart of these capabilities are the digital platforms and backbone: 5G network technology, IoT-related technologies, cloud-based applications, and systems, as well as automation and artificial intelligence, which serve as the foundation for analytics used to optimize manufacturing operations.
Since the lockdown, businesses have figured out how to operate without physically entering the plant. Businesses are shifting their focus to cloud computing, automation, and AI, and advanced analytics. Additionally, they are relocating supply chains closer to their locations and exploring alternative sources for raw materials and components.
However, despite this high level of interest and activity in predictive analytics, the adoption rate is only about 25%. This bodes well for future investment and a stronger recovery post-COVID. By 2025, the growth rate could add an additional 30% in industry 4.0 investment over what was anticipated.
What does this all mean?
One thing is certain: to reap the benefits of smart manufacturing technology, manufacturing companies will require partners who can assist them in implementing and rapidly scaling up the technology. The more providers that can assist manufacturers, owners, and operators in maximizing the value of their investment in digital initiatives, the greater the frontline adoption of these technologies.
How can Makoro™ help?
In order to accelerate deployment, Makoro™ uses a cloud-agnostic model and leverages customer’s infrastructure 100%, and deploys on the edge, in public/private/hybrid cloud, and in customer’s data centers. Makoro™ also optionally deploys on Makoro™ Cloud as a fully managed application suite.
Makoro™ Predictive Asset Performance Management solution continuously and effortlessly gathers and correlates data from the manufacturer’s internal applications, inventory management systems, and maintenance management systems. It generates recommendations for optimizing asset and workforce utilization while lowering overall maintenance costs.
The digital performance twin in Makoro™ Mind uses data from connected devices to construct the asset health and performance model and keeps it updated through periodic re-training. As a result, engineers have a complete view of how the asset is performing through real-time IoT data from the asset itself. The Performance Twin in Makoro™ helps identify potential asset problems, troubleshoot from anywhere. It integrates with Makoro™’s Recommendation System to deliver contextual recommendations to proactively improve asset performance.
And since Makoro™ provides secure access to your plant predictions, insights, and recommendations anytime, anywhere, and from any device, it plays a key role in your remote operations strategy, allowing your operations executives to make better, faster, timely, and consistent decisions about their plant operations remotely.
Schedule a demo to see what Makoro™ can achieve for your business.
May 26, 2021
Industry 3.0 pioneered the idea of automated mass manufacturing, enabling the efficient production of millions of similar goods. As the process’s pace and size grew, labor became an impediment, ushering in an era of outsourcing. Manufacturers rapidly outsourced labor-intensive operations to countries with lower labor costs.
Machines are increasingly driving production processes rather than humans, emphasizing the importance of maintenance and reliability teams.
Maintenance and reliability teams ensured that equipment met efficiency metrics over decades of service during Industry 3.0. Machines were the means of development, and technicians ensured that they worked properly.
The only drawback to this strategy was that it pitted repair and reliability teams against other development departments. For instance, if a computer was required to be shut down for recommended repairs, production would be halted as well. Though machine health could improve, production output decreased in the short term.
Considering the innovation and cutting-edge technology that Industry 4.0 uses, it’s clear that future maintenance and reliability teams will look very different from those in the past.
Manufacturers now face new demands. Usually, Industry 4.0 is synonymous with cutting-edge technologies such as artificial intelligence (AI), the Internet of Things (IoT), machine learning, and advanced analytics. But the real reason for their adoption is to drive manufacturing innovation in response to large shifts in market demand in the twenty-first century.
Consumer demand is much more diverse now than it was before, owing to the internet. A viral moment can literally cause demand to spike (or plummet). People demand more customization and sustainable production practices. When all of these factors are considered, it becomes clear that manufacturers now lag behind by 20-30 years.
Demand, sustainability, and cost pressures are all compelling manufacturers to adapt — now, not later.
Maintenance and Dependability in a Changing World:
The irony of Industry 4.0 is that while technology defines and drives it, each advancement increases the need for human input. The fully integrated factory is only a few years away.
In the near future, maintenance and reliability teams will continue to play a critical role in development. Historically, these teams were primarily responsible for planned maintenance and required repairs. That is no longer the case in Industry 4.0, where teams must optimize efficiency while remaining attentive to conflicting demands and shifting forces. Operations and maintenance teams alike will need to consider asset health holistically — both in terms of what they require to accomplish their strategic goals and how best to accomplish them.
Makoro™’s dynamic learning system takes operations management a notch up, where sets of validated recommendations with very high relevance and confidence score can be replicated across multiple locations to derive the maximum value. So instead of sharing data as reports and dashboards, manufacturers and operators share recommendations/prescriptions across locations.
Aligning Reliability and Maintenance with Industry 4.0:
Currently, maintenance and reliability teams are unprepared for the critical role they will play in development. They lack the technologies necessary to track machine health in real-time across several locations. Additionally, the use of siloed systems keeps maintenance and operations disconnected.
For all of these factors, maintenance and reliability teams would need to fully rethink their approach to manufacturing. To start with, recognize the critical role of maintenance and reliability teams in all aspects of factory operations. Second, begin equipping certain teams for the future roles they will fill. Whether by increased preparation, technology, or talent, or a combination of the three, maintenance and reliability teams will need additional resources to handle the additional responsibilities.
Makoro™’s Recommendations Dashboard tracks asset performance metrics and correlates them to recommendations in real-time. Leaders who have embraced Makoro™ have achieved more than 11% improvement in the agility of their operations.
May 24, 2021
Manufacturers worldwide are under pressure to modernize their factory workforces, but 57 percent of manufacturing leaders report that their company lacks the trained staff necessary to support digitization plans, according to a Gartner, Inc. survey.
The survey found that manufacturers are currently experiencing a challenging phase in their digitization journey towards more intelligent manufacturing.
Connected factory workers rely on a variety of digital resources and data management strategies to enhance and incorporate their experiences with their physical and virtual environments, increasing decision precision, spreading information, and reducing uncertainty.
1. Change Management is the Most Difficult Task
Complexity in the organization, integration, and process reengineering are the most common barriers to implementing smart manufacturing initiatives. When taken together, these issues represent the most significant change management roadblocks.
83 percent of respondents believe that their leadership recognizes and supports the need for smart manufacturing investment. It does not, however, reflect whether the majority of leaders grasp the scale of change ahead of them – both in terms of technology and talent.
2. Intelligent Manufacturing Needs Technology
Businesses are beginning to recognize the importance and potential of smart manufacturing. However, implementing new innovations alone is insufficient. The most critical action is for businesses to recognize that this is about more than digitization, as it entails coordinating activities for capability growth, capability enablement, and human empowerment.
3. Human capital needed for Smart manufacturing
Factory staff must adapt in lockstep with technology and be prepared for future changes. In the long run, it is critical to embed a data-driven culture in manufacturing operations through governance and training – without choking employee innovation and imagination.
Makoro™’s Dynamic Learning technologies help retain tribal knowledge. This assists in onboarding new employees and provides them with the augmentation necessary to make them better at their jobs immediately,
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May 18, 2021
This and the last year has been eventful for all sectors, but the pandemic has been particularly devastating for the manufacturing sector, which relies on the delicate balancing of supply chains to work effectively. As one of the first industries to adopt robotics, automation, and IoT, the sector has a long history of technological advancement. Manufacturers have access to an enormous amount of data.
But less than 11% of the data is used to drive business decisions.
IDC survey found several impediments to companies extracting value from their data.
The fundamental one is the lack of integration of the technology infrastructure. For instance, although the growth of IoT devices at the edge of manufacturers’ data networks has been rapid, these devices are disconnected from manufacturers’ headquarters system. Data collection points are dispersed and uncoordinated, making it hard to use data to achieve desired business outcomes such as increasing throughput. Furthermore, this still leaves Information and Operations leaders driving siloed decision making.
Deriving intelligence from data is another roadblock. Manufacturing lags behind other sectors in terms of multi-cloud and hybrid cloud adoption, and the sector also has a lower likelihood of having a central data centre. As a result, data is either discarded rather than being backed up for long-term storage or stored in long-term storage but never analyzed. Managing the storage of collected data and deriving intelligence out of it in a timely manner to drive business decision making is the second most significant problem, behind making the data available.
Ageing infrastructure is often the cause of the slowdown. For instance, data management may find it challenging to incorporate the latest sensor varieties on various factory machines. Or, the ageing infrastructure may not be capable of handling the volume of connected assets entering the facility. As a result, plants often use ad-hoc processes to link and manage assets in the absence of an underlying infrastructure that enables comprehensive management.
Additionally, a skills shortage exists. Manufacturers are confronted with an ageing workforce and a shortage of qualified workers willing to work on the shop floor. Due to the scarcity of new talent, manufacturers can only invest in upskilling current employees – which is not a bad thing on the surface but is not a long-term plan on its own. If skilled workers are the future of manufacturing, a dearth of sufficient skills is one of the most difficult obstacles to overcome.
Makoro™ alleviates these barriers to adoption.
- Makoro™ has an open architecture and can be deployed in any configuration. It can be on a fully managed Makoro™ Cloud (managed by us) or in your infrastructure in a BYOI (Bring your own Infrastructure) model or in any cloud and edge configuration.
- Makoro™ can work with a wide variety of assets and IT and OT systems. If the system has data in any form, Makoro™ can tap into that data to demonstrate value. You do not have to “big-bang” upgrade your current assets and/or infrastructure.
- Once deployed and connected to your assets and OT and IT systems, Makoro™ continuously delivers intelligence based on your data, so your data is not just stashed away without analysis.
- Natural language recommendations from Makoro™ augment your workforce. It can capture tribal knowledge, rapidly onboard new employees and enable them to be productive from day one.
#MakoroAI applies the power of #RecommendationEconomy to #SmartManufacturing, augmenting decisions related to the management of critical assets, so you can manage assets more efficiently with a lower total cost of ownership.
Ignoring the intelligence that your data could provide means passing up opportunities to expand, innovate, and boost your bottom line. Investing in intelligent operations will always have a transformative return on investment, but you need to start somewhere and start soon enough.
It is time to start collecting data and deriving intelligence. All in a single thread, and not as separate stages of the project. And then repeat this thread as frequently as you can.
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May 17, 2021
The current IoT landscape is highly OEM-centric – it is heavily OEM-data-biased and at first services the interests of the equipment manufacturer. The end customers, the asset operators, plant owners, and process owners, have been sharing their operational data with their OEM equipment suppliers in return for insights into asset conditions and improved maintenance. And depending on the strategies deployed by the OEM, the end customers and operators often have valid concerns about the credibility of these insights delivered by the OEMs. And more often than not, it is impossible to get a true understanding of the approaches that led to the insights. (Take the over-simplified example of auto-manufacturer-recommended oil change every 3,000 miles.)
However, the end customers are increasingly demanding improved equipment and process reliability across their whole asset/equipment estate. This estate includes operational assets from multiple OEM providers across the entire set of manufacturing and medical laboratory processes, across multiple geographies, with multiple technologies and wide variations in equipment age. And every organization needs a systematic and coordinated set of activities and practices which sustainably manages all its assets’ performance, risks and expenditures over their life cycles for the purpose of achieving the organizational strategic plan.
Given these conditions, reliance on OEM recommendations not only leads to fragmented asset management strategies across the estate, but these recommendations have mostly proven to be the least effective for assets with medium to high criticality.
End customers and asset operators require clear and accurate recommendations on process optimization. Unfortunately, many consider this information to be their proprietary data, their playbook, their operational cookbook, and this is confidential to their ecosystem. In addition, many manufacturing or process operations are competitive and thus deferential to their product offering and cost.
There is a trend in which end-customer business models move to a lower-cost model, with the lower deployed operational resource. However, employed process technology generally is increasing in complexity.
Makoro™, therefore, recommends and delivers continuous improvement in quality and asset/equipment total through-life cost while maintaining high process availability (OEE) and delivering a reduction in downtime based on the end customers proprietary data from their whole ecosystem while still sharing nominated data with selected OEM providers.
Makoro™ is a technology for the end-user, the asset operator.
Makoro™, by design, works with multiple and simultaneous data sources, protocols and connected and non-connected devices, legacy operational, and maintenance data. You do not have to have IoT fully deployed with every edge device reporting to get immediate value.
We sell directly to the asset operators, through process consultants and also to OEMs that recognize any IoT platform must support all the process stakeholders while protecting the intellectual proprietary of the end customer process.
We also licence our technology via API to extend the capability offering of already deployed Enterprise Asset Management (EAM), Field Service Management (FSM), Asset Performance Management (APM), Computerized Maintenance Management (CMMS) and Enterprise Resource Planning (ERP) systems.
Too many people tell you where the problem is, but shy away from recommending solutions. This is where Makoro™shines – we not only pinpoint the problem but also recommend solutions.
Makoro™ lets you take control of the proprietary data you collect from your line and your manufacturing process devices. You decide what you wish to share with the OEMs providing your equipment maintenance.
Sign up for a 10-Day Outcome Challenge to learn more about what Makoro™can do for your business.
May 14, 2021
Manufacturers will never build in the same way again as a result of Industry 4.0 – the Fourth Industrial Revolution. Manufacturers across all industries are digitizing their businesses to discover new, more cost-effective ways to source materials, run production lines, serve customers, and analyse their results for continuous improvement.
As with any significant change, Industry 4.0 may appear challenging to manufacturing professionals unfamiliar with its implications. Indeed, numerous technologies may play a role in the current revolution. The challenge is to determine which of these technologies have the greatest potential to transform the way you conduct business.
Artificial intelligence, additive manufacturing, and blockchain are three technologies that are shaping up Industry 4.0.
As with the majority of Industry 4.0 technologies, artificial intelligence, additive manufacturing, and blockchain all have one thing in common: they are cloud-based. This means you’ll have easy access to the data storage space and computing power required to analyse the massive amounts of data generated and consumed by these technologies.
Artificial intelligence (AI) assists you in resolving issues by learning from patterns in your data that you might not have noticed on your own. How is this accomplished? By combining automation and machine learning for the purpose of analysing massive amounts of data. This enables you to identify undesirable trends in machine downtime, pinpoint periods of high scrap rates, and use these insights to make more informed profit-maximizing business decisions.
Additive Manufacturing has grown in popularity even outside the manufacturing sector, with the majority of people referring to it by another name: 3D printing. Manufacturers are only beginning to explore the full range of additive manufacturing applications. Several researchers have combined machine learning and generative design to generate alternative part designs.
Blockchain technology improves transparency from raw material procurement to final product delivery and confidence at any level of the industrial value chain. Combining blockchain technology and the Internet of Things aid in resolving issues such as provenance, counterfeit identification, and asset tracking in supply chain management. It also enables new approaches to maintenance (such as digital service agreements) and faster turnaround times.
At Makoro™, we use AI & advanced data analytics to make asset performance management recommendations in the natural language of the user so they can easily understand and act upon the recommendations. This enables faster, better and compliant decision making.
May 12, 2021
Manufacturing is embarking on a data-driven revolution, but as with all transformations, realizing its full potential will take the right actions, both individually and collaboratively. Within a few years, manufacturers will collaborate in hyperconnected value networks where data and analytics technologies will drive competitiveness, new consumer experiences, and societal and environmental impact.
Indeed, data and analytics are critical to realizing the “Factory of the Future” because they allow transparency, prediction, and augmented and autonomous systems.
Already today, leading manufacturers are leveraging data and analytics to meet their performance, sustainability, and resilience goals. The imperative to increase efficiency and productivity is motivated by extreme cost pressures as well as liquidity concerns resulting from market disruptions caused by the COVID-19 pandemic. Many businesses prioritize sustainable operations – 79% have set a net-zero target, according to a recent Boston Consulting Group (BCG) survey of over 1,700 manufacturing executives. Simultaneously, businesses are attempting to create more robust and connected supply chains in order to predict and react more quickly to disruptions.
The majority of businesses are aware that data and analytics are transforming the way they produce products. 81% of survey respondents report having introduced at least one data and analytics use case, and 72 percent report that the value of data and analytics has risen over the last three years.
Despite their lofty goals and compelling value propositions, businesses have yet to realize the full potential from their analytics initiatives. Currently, only 16% of manufacturing executives report that their business has derived value from data and analytics. While the majority of companies have deployed at least some use cases, only 37% have scaled applications outside particular areas of a factory.
One factor is the focus on data. That may sound like an oxymoron, and it is. The holistic purpose of what your business needs is lost when you focus too much on the data and how it should be made available.
Instead, Makoro™ focuses on the value that your data can deliver to your business. Specifically in terms of predictions, insights and recommendations, thereby providing companies with the agility and capacity to foresee. It helps in planning for changes in process efficiency, employee engagement, and asset performance.
This results in a rapid increase in decision-making continuity and transparency.
Leaders who adopt Makoro™ report an increase in operational agility between 21% and 35%.