Damage Prevention Powered by Makoro

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 excavation damage.

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.

The effectiveness with which a company manages service demands has a significant impact on its ability to succeed. When customers have problems with the company’s goods or services, users create support request tickets. Enterprises must emphasize finding rapid and effective solutions to these problems to meet customer/user expectations swiftly and provide an improved service experience. 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. 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.

Schedule a call to talk more about your needs and how we can help.


Manufacturers must embrace the best practices of D2C digitization

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.



Intelligent Asset Management- The Next Generation

Infrastructure is critical to an operational organization, society, and country. Assets play an important role in the day-to-day life of different communities having significant social, environmental, and economic impacts in terms of capital investment, employment, quality of life, resources, energy, and services. 

Traditionally, assets have been designed and built for distinct purposes that address specific business and user requirements. This physical siloed approach responds to a trend in which different purposes are combined into the same physical infrastructure.

The main reason for this is the diversification of business and investment to generate autonomous clusters of services. Offices and hotels are merging their work‐hospitality services, correspondingly to factories and warehouses in their use of industrial space and robots. Transportation takes a similar approach, with railway stations proposing dining and shopping services to passengers whereas airports include cinema and other leisure facilities. 

Buildings are being transformed into vertical cities, with hotels, gardens, residential apartments, and commercial units spread across multiple floors and public transportation beneath. Based on the pre and post-treatment of human patients, homes and hospitals are also merging. This fusion of functionality and purpose of the built asset allows its users to play multiple roles at the same time, as the same user can be a passenger, patient, office occupant, or diner.

Intelligent asset is an infrastructure asset that

1. Is linked to information and rules that govern how it is intended to be built, maintained, used, refurbished, and demolished, and

2. Allows the asset to support or influence its own use.

Infrastructure Asset Management Challenges today:

The reason for considering an “alternative” asset management approach is that there are currently numerous challenges in managing infrastructure assets in such a way that they continue to provide value to owners and the community at large. Here are the key areas of concern that necessitate a significant change in current practices.

Why implement intelligent asset management?

The circular economy is an economic and environmental necessity, but there is a significant gap between a grand concept and a practical reality. The Internet of Things is the “glue” that connects the trillions of items we consume globally each year with the necessary changes in everyday consumer behavior, product recovery, material separation, and remanufacturing.

Inelligent assets will monitor themselves, make adjustments, and seek assistance when necessary. How can you capitalize on these advancements? The key is simplifying the approach and ensuring you have the necessary building blocks to succeed.

The amount of data surrounding intelligent assets is exploding. This information is priceless, but only if it is properly analyzed and applied. As a result, companies with intelligent assets are more likely to take wise business decisions. Organizations can achieve productivity gains, improve efficiency, and unlock new levels of innovation and operational agility by deploying a judicious mix of intelligent assets across development, operations, and business users, either fully automated or with human intervention.

Here are some of the reasons why your company requires intelligent asset management right now:

  1. Reduced downtime: Intelligent assets can provide real-time visibility into the equipment’s condition. Advanced analytics can predict and prevent production halts and other issues before they occur.
  2. Better automation: Intelligent asset management focuses on the automation of operational processes. This simplifies asset maintenance and management, reducing bottlenecks and manual labor while increasing uptime, productivity, and reducing cost.
  3. Higher productivity:  Optimizing production procedures can realize huge productivity gains, and progress can be tracked in real-time.
  4. Faster decision-making: Gather, analyze, and use the information around assets to help decision-makers make informed operational and strategic decisions with the push of a button.

Is the paradigm shift required?

The prevalence of connectivity, via the Internet of Things and the development of “intelligent assets,” will increase in the coming decade. “How can these technological advancements be used to enable more intelligent economic growth, resource, and food security, and improved infrastructure?” remains unanswered. The Internet of Things is already increasing efficiency in our current linear “take, make, dispose of” economy. Could it, on the other hand, enable a circular economy that is designed to be restorative and regenerative? Could embedding circular economy principles in smart connected systems and devices increase the opportunity significantly?

The bottom line:

Data-driven decision-making can be applied to new areas of human endeavor, according to McKinsey, because it is now possible to monitor and manage physical world items electronically. Intelligent assets, such as infrastructure, buildings, real estate, and cities, offer enhanced functionality for their various users, including residents, travelers, customers, patients, managers, or operators. According to a recent study, the potential to generate information through connected devices provides a $4.6 trillion opportunity in the public sector because of higher efficiency, innovative ways to save money, and revenues. 

In addition to providing a better user experience, the increased functionality made possible by the Internet of Things (IoT), Artificial Intelligence (AI), Big Data, Mobile Apps, Virtual Reality (VR), and 5G also supports sustainability and energy efficiency while enhancing asset management and operations for improved business economic performance

How can we help?

Makoro™ recommends and delivers continuous improvement in quality and asset/equipment through-life cost while maintaining high process availability (OEE) and delivering a reduction in downtime. 

Makoro™ also has the following benefits:

  1. Delivers dramatic improvement to overall equipment effectiveness.
  2. Delivers consistent and optimized Process, Asset, and Equipment high availability.
  3. Ensures quality and reliability for the lowest-through-life cost using our industry knowledge, expertise, and the next generation Digital-Twin and AI Technologies.

    Schedule a call to talk more about your needs and how we can help.


    Solar Wafer Manufacturing: Powering the Future with Sunlight

    Solar energy is a rapidly growing source of renewable power, and solar wafer manufacturing lies at the heart of this clean energy revolution. Solar wafers, typically made of silicon, are the foundation of solar photovoltaic (PV) cells, which convert sunlight into electricity.

    In this article, we will explore the key steps involved in solar wafer manufacturing and highlight the importance of this process in harnessing the potential of solar energy.

    1. Silicon Ingot Production:

     a. Raw Material Selection: High-purity silicon is required for solar wafer manufacturing. Metallurgical-grade silicon, typically derived from quartz or silicon dioxide, undergoes purification processes to remove impurities and achieve the desired purity level (typically 99.9999%).

    b. Purification Process: The purification process involves several steps, including crushing, grinding, and chemical treatment. The crushed silicon is reacted with hydrogen chloride (HCl) to produce trichlorosilane (SiHCl3). Further processing and #distillation yield purified silicon tetrachloride (SiCl4).

    c. Reduction and Crystallization: The purified silicon tetrachloride is reacted with a reducing agent, typically metallurgical-grade silicon, in a chemical vapor deposition (CVD) reactor. This process results in the formation of high-purity silicon in the form of solid ingots.

    d. Ingot Formation: The silicon material is melted in a crucible or quartz container at temperatures exceeding 1,400 degrees Celsius. The molten silicon is then solidified by slowly pulling a seed crystal from the melt. This method is known as the Czochralski method or the float-zone method, depending on the technique used.

    e. Ingot Slicing: The solidified silicon ingots are cut into thin wafers using wafer sawing techniques. Diamond wire sawing or diamond blade sawing is commonly employed to slice the ingots. Precision equipment is used to minimize material loss and maximize the number of wafers obtained from each ingot.

    2. Wafer Surface Texturing: 

    a. Cleaning: The wafers are thoroughly cleaned to remove any contaminants or particles that may affect the subsequent processes. This is typically done through a combination of chemical cleaning and rinsing steps.

    b. Etching: The wafer surface is textured to enhance light absorption. Different texturing methods are used, including acid texturing, alkaline texturing, laser texturing, or isotropic etching. These techniques create microscopic structures on the wafer’s surface, reducing light reflection and improving light trapping within the solar cell.

    3. Dopant Diffusion:

     a. Cleaning and Oxidation: The textured wafers undergo cleaning steps to remove any residue from the texturing process. A thin oxide layer is then grown on the wafer surface through a thermal oxidation process.

    b. Dopant Deposition: Dopants, such as phosphorus or boron, are introduced into the wafer to create the desired electrical properties. This can be achieved through various techniques, including diffusion, ion implantation, or chemical vapor deposition (CVD). The dopant concentration and depth are carefully controlled to achieve the desired electrical characteristics.

    c. Annealing: The doped wafers are annealed at high temperatures to activate the dopant atoms and repair any crystal lattice defects caused by the doping process. This step ensures the formation of a well-defined p-n junction, which is essential for the proper functioning of the solar cell.

    4. Anti-Reflective Coating: 

    a. Thin Film Deposition: An anti-reflective coating is applied to the wafer’s surface to minimize reflection losses. Different deposition techniques can be used, such as physical vapor deposition (PVD), chemical vapor deposition (CVD), or spin coating. The coating material, commonly silicon nitride or titanium dioxide, is chosen for its optical properties and compatibility with the solar cell structure.

    5. Passivation: 

    a. Passivation Layer Deposition: Passivation layers are applied to the wafer’s surface to reduce surface recombination, which can lead to energy losses in the solar cell. 

    How are solar wafers converted into solar cells?

    Solar wafers are transformed into solar cells through a series of additional manufacturing steps. Let’s explore the process of converting solar wafers into solar cells:

    1.Cleaning and Surface Preparation: The solar wafers undergo a thorough cleaning process to remove any contaminants and particles. This step ensures a clean and pristine surface for subsequent processing. Surface preparation techniques like chemical etching or texturing may also be employed to optimize light absorption.

    2. Anti-Reflective Coating: An anti-reflective coating is applied to the front surface of the wafer. This coating helps minimize reflection losses and enhances light absorption into the solar cell. Common materials used for the coating include silicon nitride (SiNx) or titanium dioxide (TiO2). The coating is deposited using techniques like plasma-enhanced chemical vapor deposition (PECVD) or sputtering.

    3. Formation of Front and Back Contacts:

     a. Front Contact Formation: A thin layer of conductive material, usually a transparent conductive oxide (TCO) such as indium tin oxide (ITO) or fluorine-doped tin oxide (FTO), is deposited on the front surface of the wafer. This layer serves as the front contact, allowing the collection of charge carriers generated by incident light.

    b. Back Contact Formation: A conductive layer is applied to the back surface of the wafer. This layer can be made of aluminum, silver, or other metals. The back contact serves as the electrode and facilitates the extraction of charge carriers from the solar cell.

    4. P-N Junction Formation: 

    a. Dopant Diffusion: The solar wafer, typically made of p-type silicon, undergoes a diffusion process to create a p-n junction. Phosphorus or other n-type dopants are diffused into the front surface of the wafer, while boron or other p-type dopants are diffused into the back surface. This creates the necessary electric field within the wafer for charge separation.

    5. Passivation: To reduce surface recombination and enhance cell performance, a passivation layer is applied to the solar cell. This layer acts as a barrier, minimizing the loss of charge carriers at the surface. Common passivation materials include silicon nitride (SiNx) or aluminum oxide (Al2O3). The passivation layer is deposited using techniques like PECVD or atomic layer deposition (ALD).

    6. Front and Back Metalization: 

    a. Front Metalization: A grid of metal contacts, usually made of silver (Ag) or a silver paste, is applied to the front surface of the solar cell. These contacts collect charge carriers generated within the cell and transfer them to the front contact.

    b. Back Metalization: A similar process is performed on the back surface of the solar cell, where a grid of metal contacts is applied to the back contact. This grid allows for efficient extraction of charge carriers from the back contact.

    7. Testing and Quality Control: The manufactured solar cells undergo rigorous testing to ensure their performance and quality. Parameters such as efficiency, current-voltage characteristics, and electrical properties are measured to verify the functionality and adherence to specifications.

    8. Solar Module Assembly: Multiple solar cells are interconnected and encapsulated to form a solar module or solar panel. The interconnected cells are electrically connected in series or parallel to achieve the desired voltage and current output. The encapsulation protects the cells from environmental factors and provides structural support.

    9. Final Testing and Packaging: The assembled solar modules undergo further testing to ensure their electrical performance, durability, and safety. Once the modules pass the quality control tests, they are packaged and prepared for shipment.

    By following these manufacturing steps, solar wafers are successfully transformed into solar cells, which are then used to create solar modules that generate electricity from sunlight.


    1. Cost Reduction: 

    • Challenge: One of the key challenges in solar wafer manufacturing is reducing the cost of production. Traditional manufacturing processes involve high material and energy costs, making solar wafers relatively expensive.
    • Solution: Several approaches can address this challenge. Implementing advanced manufacturing technologies and automation can improve  efficiency and reduce labor costs. Investing in research and development (R&D) to develop new, cost-effective materials and processes can also lead to lower production costs. Additionally, scaling up production volume and economies of scale can further contribute to cost reduction.

    2. Efficiency Enhancement: 

    • Challenge: Another significant challenge is increasing the efficiency of solar wafers. Higher efficiency means that more sunlight can be converted into electricity, resulting in greater energy generation and improved overall system performance.
    • Solution: Advancements in wafer technology, such as using thinner wafers textured surfaces, and improved light-trapping techniques, can enhance the efficiency of solar wafers. Additionally, incorporating new materials, such as perovskite, with higher conversion efficiencies can also improve the overall efficiency of solar cells.

    3. Environmental Impact: 

    • Challenge: Solar wafer manufacturing processes can have an environmental impact due to the use of hazardous chemicals, water consumption, and waste generation.
    • Solution: Implementing cleaner production techniques and adopting environmentally friendly practices are essential. This includes the adoption of green solvents, waste reduction strategies, recycling and reuse of materials, and water conservation measures. Emphasizing sustainability throughout the manufacturing process, from raw material sourcing to waste management, can significantly minimize the environmental footprint of solar wafer manufacturing.

    Bottom Line- 

    Solar wafer manufacturing plays a vital role in the production of solar cells, enabling the harnessing of clean and renewable solar energy. Advancements in solar wafer manufacturing techniques continue to improve the efficiency and affordability of solar energy, driving its widespread adoption and contributing to a sustainable future powered by sunlight.

    Schedule a call to learn more about how Makoro™ can help you improve efficiency by creating a more sustainable future. 


    Total QA through Autonomous Machine Vision

    Total QA is seriously interesting and until last year only talked about. Now with advancement in Autonomous Machine Vision, Total QA is not just a concept – it can be realized by manufacturers themselves, and it can be implemented and realized value from very quickly.


    Hot: Makoro™ Alpha Preview

    CodeData is launching an alpha release of the Makoro™ product line on December 15 at the Startups Club Demo Day event in Bangalore, India. Information on the demo day is at the Startups Club site. Once you sign up for the event we will do a quick demo of the Makoro™ Alpha product and answer any questions you may have. If you can’t make it to the event, reach out to us @ info@codedata.io and we will set up an online demo for you.


    Artificial Intelligence in conventional manufacturing

    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.