News & Updates
March 21, 2022
Excavators, Utilities & One-call Centers – all stand to gain with Damage Prevention Powered by Makoro™
Artificial intelligence (AI) has altered how businesses maintain, monitor, and construct infrastructure. In the damage prevention sector, advancements such as 24-hour monitoring systems, gas leak detection equipment, and improved safety gear have all contributed to the safety of construction sites and infrastructure projects.
Often ignored in the realm of damage prevention is the use of artificial intelligence (AI), which may be used to optimize ticket processing, monitor all sources of information, develop statistical safety models, and expedite on-site repairs to damaged utilities. When AI is utilized in applications such as 811 call centers and on-site personnel, it has the ability to mitigate risks, detect damage trends, and ultimately eliminate excavator damage.
Due to the volume of tickets generated daily, the ticket processing system at many contact centers may swiftly deteriorate from a trickle to a torrent. Makoro™’s pioneering AI-Digital-Twin-based recommendation technology provides the damage prevention industry with a transformative continuous intelligence platform, which combines Artificial intelligence (AI) with Advanced Analytics to analyze tickets for risk indicators.
In the U.S. an underground utility line is damaged every six minutes. MakoroTM Mind – the underlying AI and Advanced Analytics Platform for Makoro™, aggregates, correlates data from Geographical Information Systems, assets deployed in the field, and data generated by utilities, excavators, locators, and makes recommendations to mitigate risk in real-time.
MakoroTM automatically categorizes tickets into risk profiles and populates schedules of one-call center personnel based on the risk assessment. Moreover, Makoro™’s predictive analytics makes predictions of damage based on utilities around job sites and the risk record of excavators.
Not only does Makoro™ provide total insights into the operations of asset owners, operators, and call centers, but having a system that learns continuously from the root cause analysis of damages and damage tickets enables our customers to make better safety recommendations and constantly enhance operational efficiency.
While artificial intelligence has a variety of uses in the damage prevention business, one thing they all have in common is the collection of correct data to aid in determining predictability.
Regardless of whether AI is used to identify or warn employees of potential hazards, workers stand to gain from better safety recommendations based on Makoro™’s Continuous Intelligence platform. For damage monitoring systems such as the DIRT Report, Artificial Intelligence has the potential to change how One-Call centres and national organizations measure, report, and act to mitigate future damages.
Makoro™ leverages customers’ existing infrastructure investments (cloud, on-premise, or hybrid) and interacts effortlessly with the customer’s existing private/public/hybrid cloud, on-premise, and edge systems.
January 17, 2022
- Consumer-driven Manufacturing
Consumer preferences fluctuate at the same rate as technology advances, making it challenging for producers to respond rapidly enough to provide in-demand goods and services.
Modern clients want, at the absolute least, same-day delivery, customised goods and services, and transparent delivery systems. However, distinguishing your firm and being internationally competitive demand a degree of agility and flexibility that conventional business models are incapable of providing.
Rather than that, consumer-driven manufacturing is concerned with predicting the demands of consumers who will use your goods. However, how is this possible? By incorporating new technologies and capabilities into your current systems and software, such as data analytics, the internet of things (IoT), and artificial intelligence (AI), among others.
Manufacturers may boost operational efficiency and deliver goods to customers faster by using tactics such as digital quality control, asset location monitoring, and automated material replenishment. Users and stakeholders may tailor their digital interaction experiences using these tools.
- Predictable and Reliable Supply networks
Manufacturers are confronted with a period of dynamic market supply and demand fluctuations. According to Deloitte, the majority of buying managers continue to face system-wide challenges as a result of increased customer demand, increasing material and freight prices, and sluggish delivery.
While disruptions are inevitable and expensive, many firms are developing methods to improve the predictability of supply chains and logistics. By replacing human operations with technology like as artificial intelligence, data analytics, and sensors, supply chain managers can discover trends, forecast purchase requests, and manage inventories more effectively. According to Deloitte, “digital supply networks and data analytics can be effective facilitators of more flexible, multi-tiered disruption solutions.”
- Connected services
While technology improves company processes, it also alters the products and services manufacturers can provide their consumers.
Connected services are extra offers centred on internet-connected objects such as healthcare gadgets, cars, hand tools, industrial, and even wind turbines. Capgemini notes in an evaluation of connected services in manufacturing sectors, “We see business models evolving toward pay-per-use and pay-per-output models, in which consumers pay not for the product itself but for the advantages it provides.”
Although the possibilities for connected services are limitless, some of the more well-known examples include remote management of equipment and machinery through car telematics, maintenance forecasting, smart home technologies, and automation.
Offering connected services improves the consumer experience and enable manufacturers to distinguish themselves from their competitors. Data collected at each stage of the client journey may be utilized to constantly enhance the quality of the goods and services you produce. Additionally, connected services provide consistent income streams and greater margins.
- Intelligent factories
Smart factories, also known as digital factories or intelligent factories, include highly automated and self-adapting technology and machinery to maximize efficiency and adaptability. Sensors monitor goods and inventories, while cloud-connected machinery and equipment give real-time visibility into maintenance requirements.
Adidas is only one example of a company that is forward-thinking. Adidas’ “speed factory,” which aims to establish a factory of the future, is equipped with 3D printers, robotic arms, laser-cutting robots, and Internet of Things capabilities for fast creating mockups and digital copies. Adidas can rapidly print prototypes with the assistance of automation and robotics to satisfy changing customer expectations with shorter lead times.
- Industry 4.0 and the emergence of the digital economy
We are in the midst of the fourth industrial revolution, sometimes known as Industry 4.0. While the third industrial revolution pioneered the development of digital technology, Industry 4.0 is defined by hyper-automation, the Internet of Things, smart factories, and big data. These breakthroughs have sparked the birth of a digital economy, a global economy built on digital technology.
According to TechTarget, “the fourth industrial revolution builds on the digital revolution by bridging the physical and cyberworlds.” Manufacturers have an infinite number of options to adapt business models, enhance processes, and complete jobs quicker and better than ever before.
The digital economy encompasses businesses, goods, and services that would not exist in the absence of advanced digital technology – such as Netflix, Spotify, Airbnb, Uber, and Lyft. And as technology advances, so does the competitive environment. Do you remember Blockbuster Video? By introducing streaming services, Netflix was ahead of the digital curve, whereas Blockbuster trailed far behind. Today, only those who were alive in the 1990s remember Blockbuster, yet everyone appears to have a Netflix subscription.
Consider improvements in healthcare device production. Historically, blood glucose metres were battery-operated, analogue devices that lacked internet connectivity. Nowadays, the majority of these technologies are completely integrated into the digital world. Manufacturers get new information, consumers can monitor their own health, and healthcare practitioners can better satisfy their patients’ requirements.
- Circular Economy
Manufacturers are expected to supply items quickly and on a global scale, putting an inevitable strain on our environment. According to the World Economic Forum, manufacturing in the United States accounts for 23% of the country’s direct carbon emissions, whereas European production generates 880 million tonnes of carbon dioxide each year.
This is because factories have historically operated on a linear “take-make-trash” paradigm that is based on fossil fuels, over output, and waste. However, an increasing number of firms are embracing the circular economy, a sustainable model that maximizes efficiency at every step of production.
The circular economy makes use of cutting-edge technology such as artificial intelligence and machine learning to automate processes, simplify operations, and boost efficiency. Each step of production is subjected to recycling, refurbishment, and remanufacturing procedures in order to decrease waste and expenses, hence lowering a company’s carbon footprint. Additionally, digitizing processes provide real-time information that enables firms to stay on top of their sustainability targets.
Hyperautomation is defined as “a business-driven, disciplined methodology that businesses utilize to swiftly discover, vet, and automate as many business and information technology activities as feasible.”
Hyperautomation is enabled by the coordinated use of technologies such as artificial intelligence (AI), sensors, machine learning, robotic process automation (RPA), low-code development platforms, and business process management (BPM) tools. This tendency is prevalent across previously segregated processes such as engineering, manufacturing, and system and software management in information technology.
Manufacturing occurs in highly compartmentalized settings, and many firms continue to depend on manual, time-consuming procedures. Hyperautomation automates formerly manual procedures and increases operational transparency. While technology takes care of routine but critical duties, your human staff can concentrate on more challenging responsibilities, such as fostering innovation.
January 13, 2022
Manufacturing is rapidly reviving, unfazed by substantial labor and supply chain issues. To continue this pace, producers must balance increased risks with a commitment to sustainability. Our 2022 forecast delves into five manufacturing industry trends that will assist firms in transforming risks into opportunities and capitalizing on growth.
- Manufacturing will transition from infrequent use of smart factories to widespread adoption: Until date, a fully smart factory with integrated solutions has remained elusive owing to gaps in offers and a lack of suppliers capable of meeting all of the technical requirements necessary to realize a smart factory. However, with the entry of hundreds of start-ups, technology has become more cost-effective. Multiple companies now provide technology and solutions like video analytics, artificial intelligence, cybersecurity, autonomous mobility robots, and command centers that formerly required unique and often in-house development. Each component of the technological puzzle has several alternatives.
Starting in 2022 we expect a significant transition from companies with a few smart factory components to those with production environments that are smart.
- FOMO will drive organizations. Fear of Missing Out will play a significant role in driving smart factory adoption in 2022. Organizations are quickly realizing that delaying digital transformation is not an option and that if they do not act soon, they will lose their competitive edge. These organizations will be more receptive to significant adjustments in people, processes, and technologies that will catapult them ahead of their competition.
2022 marks the year when manufacturers will start demonstrating value from their adoption of smart and sustainable manufacturing practices.
- Actions based on data will grab the spotlight. Manufacturers are becoming more acquainted with data from different sources, in different shapes and forms, which is necessary for the operation of a smart factory. True smart factories will include command centers — envision numerous control towers — that will bring data from throughout the company together in ways that businesses have never been able to accomplish before. Data has always been the forte of manufacturing companies, but it has been the usage of this data to drive sustainable and optimized production that has been a challenge in the past.
Through this year, we see companies making significant steps to act on data, bridging the divide between technology and people.
- Vision systems and autonomous mobile robots will be critical components of the smart factory. Organizations cannot afford quality faults as material prices continue to rise. Vision systems will become more important in detecting errors or faults immediately before they affect the whole manufacturing process. This will result in considerable quality and safety gains and will play a vital part in lean transformation. Another critical technology will be autonomous mobile robots (AMRs), which have the potential to significantly increase productivity by automating routine chores. Whereas a corporation may have a few dozen replenishment experts on staff today, that number may soon drop to zero.
We see remote operations and safety requirements for frontline workers driving the adoption of smart manufacturing technologies in 2022
- Workforce augmentation will become crucial. For at least the next two years, the labour shortfall will endure and, in all likelihood, deteriorate before improving. This will increase the need for technology adoption in order for businesses to continue operating and meeting client expectations. Along with smart factory adoption, firms may gain a competitive edge by anticipating how important manufacturing positions will change and developing strategies for improved hiring, training, reskilling, and upskilling for these roles.
2022 is the year for empowering the frontline workforce while building upon the tribal knowledge that manufacturers have accumulated for years. Workforce augmentation is a key recipe for success in onboarding a younger and more agile workforce.
Each manufacturer should evaluate their readiness for The Year of the Smart Factory. If the answer is no, extensive due diligence on their smart factory potential should be done. One point is clear – they need to get started in order to stay ahead.
How can Makoro™ assist?
Makoro™ optimizes industrial supply chain processes by providing continuous insights and recommendations through Makoro™ Mind, the data-driven core that leverages IoT, Digital Twin, Artificial Intelligence, and Advanced Analytics to provide operational suggestions.
Natural-language recommendations from Makoro™ are built for the frontline workers so that they can understand and act upon them.
Additionally, Makoro™ leverages customers’ existing infrastructure investments (cloud, on-premise, or hybrid) and interacts effortlessly with the customer’s existing private/public/hybrid cloud, on-premise, and edge systems.
By correlating real-time asset, maintenance, and workforce parameters with suggestion sentiment, acceptance, confidence, relevance, and originality, the Recommendations Dashboard demonstrates Makoro™’s ongoing value to manufacturers’ operations.
October 29, 2021
The supply chain has become more complex as products flow up and down from/to various points more frequent basis. Numerous parties participate in the product supply chain and possess a wealth of knowledge and data. Industries must maintain product quality in order to safeguard their brand and to compete better. A rapid recall of a product can save a person’s life when a product that is directly tied to their health is discovered to be contaminated or of poor quality. In this instance, the producers must pinpoint the source of the problem and the product’s position. These are some of the challenges that necessitate product visibility across the supply chain. And traceability is a system that enables the resolution of all of these concerns. Traceability refers to the ability to track an entity’s history, application, or location throughout the supply chain using recorded identification.
Challenges faced during implementation
One of the major challenges faced in implementing Traceability is the technology & data
While technology is expanding its reach while there are still a lot many warehouses still operate with paper at the integral points, although RFID chips and scanners are now conveniently available.
Among the factors impeding technology adoption include company executives’ lack of knowledge,the belief that it is a fad, and a desire to wait for wider acceptance before committing. Even company executives who see it as a promise are hesitant to spend money and effort in it due to the absence of industry-wide standards and processes.
Thus, for it is to be effective, it is necessary for everyone in a typical supply chain business to be convinced of its benefits; key stakeholders must be on board and see the value in using it. As a result, market acceptance is a critical issue to address.
Complex worldwide supply chains, entail a large number of unrelated actors—producers, brokers, transporters, processors, wholesalers, retailers, and consumers—who may lack trust in one another. This has a significant impact on the level of collaboration. For instance, these players may be reticent to exchange data and/or engage in direct relationships or intermediaries that would facilitate the transmission, validation, and reconciliation of data across multiple parties. Business frameworks that enable coordination among these numerous participants are essential.
A significant difficulty in traceability is ambiguity in product information, which results from the recording of ambiguous and unclear product features that are difficult to track. This might be a result of inefficient and largely manual record-keeping, supply chain complexity, or identification lag time. Particularly difficult is the process of blending or comingling ingredients, or the utilization of a raw resource to generate a semi-finished or final culinary product. Traceability issues can also develop when items change their IDs or ownership, are repackaged, or transit international boundaries using different naming and labeling procedures.
Why Traceability is important in the current world
Having complete information on a product from conception to completion is critical for any business’s success. A traceability system is the finest instrument for obtaining and disseminating that information. It enables all supply chain actors to add value to the manufacturing and distribution processes. From product planning through disposal, and therefore to accomplish innovation in the product design process. Several of the system’s primary benefits are listed below
- Transparency: To plan and act effectively, supply chain actors must be aware of the product’s know-how status. The product’s users must be informed of all pertinent information, such as the product’s ingredients, processing history, date of manufacturing, and country of origin. The entire manufacturing process, from conception to completion, should be accessible, allowing actors to access this information at any time. Traceability contributes to supply chain transparency
- Quality Control: Customer happiness is critical for a business to remain competitive. The consumer is satisfied when they have trust in using the product and can obtain all necessary information about it. The company’s quality control method must be zero-tolerance throughout the product manufacturing process. Whenever a quality-related issue is brought to the attention of any actor along the supply chain, appropriate and immediate action must be made to enhance the design and manufacturing process in order to implement the necessary corrective actions in the subsequent lot or batch of production. To accomplish this, the players must trace back the supply chain and determine where and when production failures happened. A traceability system that includes a capability for tracing back helps actors manage the quality control process.
- Decrease time to market: A traceability system keeps track of all pertinent information at each stage in the supply chain, establishing a link between all divisions within a business, from order processing to inventory management, processing, packing, warehousing, and despatching. This information enables actors to act in a timely manner, ensuring that all required products are made and delivered on time. This contributes to the total cost reduction of the manufacturing process, hence increasing the company’s profit.
- Combating Product Counterfeiting and defending brand: A company develops a brand over time by producing novel products, maintaining a high standard of quality, and thereby garnering client happiness. This brand will vanish in an instant when counterfeit products bearing the same trademark but with inferior quality enter the market. Traceability enables the tracking of the original product along the supply chain, assisting actors in combating product counterfeiting.
- Increased SCM efficiency: Traceability systems contribute to supply chain management process efficiency by decreasing costs, primarily logistics, by giving complete information from product conception to retail in the market. This enhancement fosters collaboration among supply chain actors, thereby strengthening their economic and technical capabilities.
- Strengthen relationships with consumers: As previously stated, customer happiness is critical to corporate success, and satisfaction is obtained when we communicate with customers. The more information we supply to customers, the more connected they will get with the product and its producers. With an effective traceability system in place, consumers may access product-related information at any time, assisting actors in maintaining contact with them.
- Increase competence: Knowing a customer’s purchasing behavior enables a business to make the goods on time and launch it appropriately in the market. A retailer’s traceability database enables him to determine which products are sold in what quantity and during what season. Similarly, he is aware of the type and brand of the goods sold and can thus determine the quantity of a particular product to order at what time to suit the customer’s expectations. This assists him in developing the confidence necessary to compete against competitors. It may also be a source of competitive advantage for supply chain partners, as traceability systems aid in increasing SCM efficiency by resolving product safety issues. It also assists the company in comprehending its logistic system and enabling them to create high-quality items on time.
Increasingly competitive marketplaces require businesses to have agile, effective, and efficient supply chain management processes. To accomplish this, businesses must have access to product data and information throughout the supply chain. They can track the location of products downstream and the processing history and other treatment of products upstream in the supply chain using an automatic traceability system. However, today’s supply chain is complex, with all actors geographically distributed throughout the world. They lack familiarity and trust with one another and hence are averse to sharing critical information on a global scale. This is a significant obstacle to creating an effective traceability solution.
Businesses that invest in powerful traceability capabilities will be able to deliver the right product to the right location at the right time. All this with the appropriate level of customization and speed—all at a competitive price. Additionally, they will be able to meet critical sustainability expectations and regulatory needs from stakeholders. Additionally, they will be more resilient to supply and demand shocks. These capabilities will drive significant growth and profitability, as well as enable the development of new business models.
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.
July 1, 2021
Smart factory development is a top priority for manufacturers across all industries and sectors. It is a component of a business’s digital transformation, and it is critical to maintaining competitiveness while also meeting the demands of consumers and end-users, as well as B2B customers and regulators.
This is all part of Industry 4.0, the umbrella term for the revolution currently sweeping the manufacturing sector.
As with previous industrial revolutions, Industry 4.0 will evolve over many years and decades as new technologies and processes are developed, and as businesses, regulators, and consumers grow.
What are the critical smart factory developments worth examining today if you work in the pharmaceutical or medical technology industries?
Why is Industry 4.0 even more critical to the pharmaceutical manufacturing industry?
- Increased Productivity — Automating processes enables them to be completed more quickly and accurately. Reduce downtime through automation and the use of sensors and predictive systems that enable equipment to function autonomously.
- Improving the supply chain’s efficiency through integration – They are making it feasible to transition from batch to continuous manufacturing, a production approach that results in much less downtime and increased efficiency.
- Increased Quality – Increased automation and continual monitoring of your manufacturing plant will result in fewer mistakes and higher-quality final products.
- Risk Reduction – This follows naturally from the preceding two arguments – increased manufacturing precision reduces the danger of substandard items reaching end customers.
- Facilitates Regulatory Compliance – Compliance with existing and upcoming laws in the E.U. and other parts of the globe is made more accessible via the use of Industry 4.0 technology. To comply with the Falsified Medicines Directive, new track and trace systems and serialization solutions are presently being deployed.
- Improved Business Oversight – Industry 4.0 technologies enable real-time reporting, increased data collection, improved data analysis, and improved data presentation in usable formats.
- Development Of New Business Prospects – Industry 4.0 will also open up new commercial prospects for pharmaceutical businesses. For instance, Industry 4.0 technologies enable seamless and highly efficient end-to-end supply chain integration. This increases productivity, which helps your business immediately. A more connected and efficient supply chain, on the other hand, is also more scalable, opening up new potential for your organization. Covid-19, a quick-win situation.
- Increased Profitability – When all of the aforementioned are combined, the outcome is improved corporate profitability. Additionally, your firm will be more competitive and better able to address future difficulties and opportunities. Covid-19 has accelerated the advancement of biotechnology problems.
The pharmaceutical industry has only recently begun to adopt Industry 4.0 technologies, despite the fact that it has been using batch manufacturing for more than 50 years. However, the traditional batch process technique has been demonstrated to be lengthy: after each stage in the process, production is generally halted to allow for quality assurance testing of the material. Each break lengthens the lead time and increases the likelihood of defects and errors (FDA, 2016).
This encouragement comes at a critical time – we are entering an era of precision (personalized) medicine, “where medicines must be produced with unique characteristics and made available to people in need more rapidly.” (U.S. Food and Drug Administration, 2016).
To create customized medications, pharmaceutical companies no longer need to produce large batches but rather tiny ones tailored to a limited group of individuals who require a certain treatment in a specific dosage. Batch production is not the answer to these demands, but continuous manufacturing that is connected, smart, adaptable, and accurate.
Continuous manufacturing is used in the pharmaceutical business to move substances nonstop inside the same facility, eliminating wait times between process steps; the materials are fed via an assembly line of integrated components. Manufacturing that is continuous “saves time, decreases the risk of human mistakes, and enables a more agile response to market changes. It can operate for an extended length of time, potentially reducing the probability of medication shortages.” (U.S. Food and Drug Administration, 2017).
Pharma Opportunities 4.0
- Gains in economic terms, such as greater revenues as a result of reduced transaction costs
- Increased reliability and consistency in production and output, as well as higher-quality products
- Energy-efficient and ecologically friendly manufacturing systems
- Utilization of human and material resources effectively.
- Changes in work structure, with a greater emphasis on remote, flexible, and on-demand labor
Pharma 4.0’s Obstacles
- Gaps in infrastructure
- Policies and regulations that are out of date and do not take into account 4.0 Industry
- Ownership and security of data
- Transparency, confidentiality, and ethics
- Changes in the fundamental characteristics of innovation processes and their implications for competition and entry barriers
Take away points
We may now re-evaluate our industry’s accomplishments while simultaneously re-strategizing our future strategy toward offering high-quality therapy at scale and bringing fresh hope to humanity.
By strategically integrating the production process, we as an industry will be able to stay ahead of the problems and expectations on which the rest of the world is so reliant.
Predictive analytics enables you to foresee issues, minimize risks, capitalize on opportunities, and ensure that resources are directed appropriately.
Predictive analytics is already being used by pharmaceutical and medical device makers in the field of equipment maintenance. It is possible to forecast the effect of a variable on a piece of equipment, a production line, or a process using technology such as digital twins.
Makoro™ leverages #AppliedArtificialIntelligence and #NaturalLanguageRecommendations powered by #DigitalTwin in solving transformative problems in the manufacturing supply chain.
If you are still leading with reports and dashboards, you are falling behind. You are leaving money at the table. When you can shave off minutes and hours you spend making the right decisions on your assets.
Asset performance recommendations from Makoro™ deliver improved asset and process performance consistently through recommendations. These recommendations are backed by data and can be traced to the sources of data.
Makoro™ recommendations deliver direct operations savings and indirect compliance savings.
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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