If you’re in the Northern Hemisphere, Winter is Coming.And if you’re a diehard cyclist, that also means you’re going to face challenges beyond the cold. Bike paths – just like the adjacent roads – can get mucked up with potholes, ice, and (like your driveway) blocked when a snowplow makes an errant dump.In the future, cities will have a new tool at their disposal to help ensure cyclists can have the best thoroughfares possible in the depths of winter. It’s called the Street Smart Robot, and it was designed and built by the InDro Robotics engineering team at Area X.O in Ottawa. We believe it’s a great example of how robotics can help make future Smart Cities safer, more efficient, and more liveable for all of us.It was a complex build from the ground up, requiring a lot of work on Machine Vision and obstacle detection and avoidance. Here’s a sneak peak we released while development was still underway:<iframe width="640" height="360" src="https://www.youtube.com/embed/I1MTJHVsIKA??si=Bw1lA0hTFdqh2x3B&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe><h3 id="isPasted">Funding</h3>Research and Development companies like ours are often fortunate enough to receive funding to assist with projects like these. Our concept for the Street Smart Robot caught the attention of the <a href="https://www.ovinhub.ca/" target="_blank">Ontario Vehicle Innovation Network</a> (OVIN). Its <a href="https://www.ovinhub.ca/" target="_blank">website</a> describes the agency as “Ontario’s flagship initiative for the automotive and mobility sector…driving economic development and catalyzing a future that builds safer, cleaner, and more efficient transportation.”OVIN committed $465,000 to the SSR project.<div title="Page 1">“With a world-class innovation ecosystem, Ontario continues to lead in the development of new mobility technologies and solutions,” said Vic Fedeli, Minister of Economic Development, Job Creation and Trade in our <a href="https://indrorobotics.ca/wp-content/uploads/2024/12/InDro-Robotics-Street-Smart-Robot-News-Release.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">news release</a> about the project. “InDro Robotics’ prototype Smart Street Robot represents the best of our province’s cutting-edge tech research and development that is creating solutions for real-world challenges, and we congratulate them on this milestone.”OVIN also weighed in:<div title="Page 1">“Ontario is home to innovators and game-changers that are shaping the future of mobility on the global stage. The growth of multi-modal transportation, combined with weather-related challenges, presents a unique opportunity for Ontario companies to commercialize leading-edge solutions that make our roads safer and travel more efficient,” said Raed Kadri, Head of OVIN. “This groundbreaking technology showcases the unparalleled caliber of Ontario SMEs in addressing significant mobility challenges—and more broadly, the province’s capacity to foster innovation and accelerate their time to market.”&nbsp;<h3>Networking</h3></div>Robots like the SSR require more than just good sensors and compute. They also require an exceedingly reliable 5G network in order to accommodate the dense data throughput required. Here, we partnered with <a href="https://www.rogers.com/" target="_blank">Rogers Communications</a> for networking hardware and technical support.</div><div title="Page 1">“Rogers is proud to work alongside InDro Robotics and OVIN to improve public safety,” said Tom Turner, President, <a href="https://www.rogers.com/business" target="_blank">Rogers Business</a>. “By leveraging the <a href="https://www.rogers.com/business/iot/wireless-private-network" target="_blank">Rogers 5G Hybrid Wireless Private Network</a>, we’re able to help build safer communities through real-time detection and reporting.”Robust, high-speed networks are crucial for Smart Cities – where a multiplicity of interconnected devices will be constantly relaying data. This will be especially true as more connected and autonomous vehicles like the Street Smart Robot start sharing roadways (or bicycle paths) with people and other traffic..“The Street Smart Robot is designed to greatly enhance the safety of bicycle lanes, particularly during winter. InDro is pleased to have partnered with Rogers and OVIN on this endeavour,” says InDro Robotics Founder/CEO Philip Reece.Below: The SSR incorporates LiDAR and 3D depth cameras to help sense its surroundings – and to avoid cyclists, pedestrians and obstacles<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1733845991303-SSR-LiDAR-Units-scaled.jpg.webp" style="width: 100%px;" class="fr-fic fr-dib" alt="SSR LiDAR"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1733846026679-SSR-Depth-Camera-scaled.jpg.webp" style="width: 100%px;" class="fr-fic fr-dib" alt="SSR Depth Camera"><h3 id="isPasted">InDro's Take</h3>This is actually just the beginning of the Street Smart Robot’s journey. This is the prototype version, and we are already looking at ways to further enhance the product prior to commercial deployment. We’ve learned, for example, that while the existing tread locomotion is great for heavy snow and ice that an all-wheel drive wheeled platform will provide greater agility and speed. We are also looking at a smaller and more human-friendly form factor.That being said, our SSR V1 has proven itself for Simultaneous Localisation and Mapping (SLAM), as well as detecting hazards that could cause cyclists problems.“Safer streets for everyone – including cyclists – are part of the Smart City of the future,” says InDro Robotics Founder and CEO Philip Reece. “The Street Smart Robot is an important step along that road.”We’ll have more to say about our Street Smart Robot when we release V2 in the future. So stay tuned – and, if you’re cycling, stay safe.</div>

A new robot to help ensure cyclists can have the best thoroughfares possible in the depths of winter.

InDro's Street Smart Robot Built to Keep Cyclists Safe in Winter

Using technological tools can help you schedule machine maintenance in a predictive manner, which will help to improve the efficiency of your maintenance team.<a title="Preventive" href="https://www.rowse.co.uk/blog/post/what-is-predictive-maintenance" target="_blank" rel="noopener">Preventive, preventative or predictive maintenance</a> is the strategy by which you can reduce the chances of equipment failure and unplanned downtime. You can apply it across the whole facility, including machinery, electronic equipment and vehicles. Planning ahead will help you achieve greater long-term cost and energy efficiencies, so creating a preventive maintenance schedule to benefit your entire business strategy.<h2 dir="ltr">How To Create A Preventive Maintenance Schedule</h2>A preventive maintenance schedule is a detailed list of your equipment and repairable assets. It should set out the frequency of inspections and regular maintenance tasks you need to carry out to keep these items always in the best possible working order. Repair crews and technicians should be equipped with precise instructions to guide them through this process, with clear deadlines for its completion.You’ll need a maintenance manager or supervisor to monitor the schedule and keep an adequate stock of spare parts to cover possible repairs. They’ll also have to match up the maintenance requirements to the available resources at your facility. This includes matching the availability and skills of your team as closely as possible to each maintenance task.<h2 dir="ltr">Plan Or Schedule?</h2>You or your director of operations will usually be responsible for coordinating an overall preventive maintenance plan. This ensures that the goals of your maintenance team are aligned with your business goals, focusing on the bigger picture of what needs to be done.Your maintenance manager or supervisor will be in charge of the preventive maintenance schedule. This ensures the plan is successfully executed. The schedule concerns what work needs to be done, when, how often and by whom.To create a preventive maintenance schedule, follow these five main steps:<h3 dir="ltr">1. Inventory</h3>First, determine which of your assets need routine maintenance:<ul><li dir="ltr">Is an asset more prone to failure with age?</li><li dir="ltr">Could you prevent failures by regular inspection and maintenance?</li><li dir="ltr">Is this asset a critical factor in your business operation?</li></ul>Any asset answering yes to these points should be included on your inventory list, which can form an electronic catalogue or spreadsheet. Include full information on each item of inventory, such as the make, model and serial number, plus the asset’s location, maintenance history and necessary spare parts.&nbsp;<h3 dir="ltr">2. Prioritise</h3>If you have a substantial operation, it will take time to create preventive maintenance schedules for all your assets. This means strict prioritising so that you deal first with your most essential assets. You can do it systematically by calculating the levels of each asset’s risk, taking into account factors such as the likelihood of the risk being detected, the probable frequency of failures occurring and the potential severity of a failure. You can assign a numerical ‘weight’ to each factor by calculating its&nbsp;<a title="Risk Priority Number" href="https://www.6sigma.us/six-sigma-articles/risk-priority-number-rpn/" target="_blank" rel="nofollow noopener">Risk Priority Number</a>.<h3 dir="ltr">3. Establish Intervals</h3>Most of your assets are likely to require different intervals between scheduled maintenance – and there are different ways to deal with this. For some items, a floating time-based schedule will work best, but for others, a meter-based schedule is preferable. You should always refer to the manufacturing manual and previous maintenance data to determine what maintenance interval is appropriate for all items of equipment.<h4 dir="ltr">Time-Based Schedules</h4>Time-based schedules are calendar-based so that maintenance is performed according to set periods – e.g. every week, every month, etc. These can be further divided into fixed or floating time scheduling. Fixed is when you schedule maintenance after a set and unchanging period, ignoring variables such as whether the last maintenance was completed on time. Floating means that you schedule maintenance in direct relation to the last time it was performed.<h4 dir="ltr">Meter-Based Schedules</h4>Meter- or usage-based scheduling can be simpler, especially if your equipment is controlled by a PLC or other device. In this case, maintenance is triggered when the asset reaches a certain preset threshold, such as the number of production cycles performed or hours operated. It incorporates a certain amount of flexibility, to allow cycles to complete before undertaking maintenance.<h3 dir="ltr">4. Schedule Recurring Tasks</h3>Recurring tasks and inspections are important when establishing a preventive maintenance schedule, so plan carefully. You can do this on paper, on a computer spreadsheet or by using proprietary software, depending on the size of your operation and its maintenance requirements. Preventive maintenance software is the easiest because it allows you to set up the tasks, intervals and instructions for every item and then relax until you get an alert on your calendar.<h3 dir="ltr">5. Monitoring</h3>It’s essential to monitor your maintenance schedules regularly to ensure that each piece of equipment is properly maintained. You can assess the failure frequency to see if it’s dropping since you implemented the schedule. If you’re still experiencing frequent failures, the maintenance frequency may need adjusting. Alternatively, you may find that you need to scale back if routine maintenance is being performed too often.<a title="Metrics" href="https://servicechannel.com/blog/essential-maintenance-metrics/" target="_blank" rel="nofollow noopener">Some metrics</a> you can use to monitor your schedule include the Mean Time Between Failures, which should increase if your schedule is working effectively. Overall Equipment Effectiveness tracks the equipment’s availability, performance, and quality, while Planned Maintenance Percentage is a measure of lateness if a preventive maintenance task is overdue. This may indicate that you have insufficient maintenance staff or identify other deficiencies.&nbsp;<h2 dir="ltr">Why Creating A Preventive Maintenance Schedule Is Important</h2>A preventive maintenance schedule is vitally important in keeping your operations running smoothly and successfully. It will make your maintenance operations more systematic, providing your maintenance crews with guidance and structure, thus increasing overall team efficiency. You’ll reduce&nbsp;<a title="Downtime" href="https://www.rowse-automation.co.uk/blog/post/how-to-reduce-equipment-downtime" target="_blank" rel="noopener">unscheduled equipment downtime</a>, so preventive maintenance will extend your equipment’s lifespan. Creating an effective preventive maintenance schedule on any scale can deliver great benefits to your organisation.

Preventive maintenance is a key factor in the running of industrial facilities. While it’s always been sensible to inspect and check your equipment for faults and repairs, the advent of Industry 4.0 has made it a far more effective business practice

How To Create A Preventive Maintenance Schedule

Quality control in manufacturing is no easy task and too often involves learning from hindsight. By the time parts churn off the assembly line and undergo inspection, it might be too late to catch problems. Waiting until the tail end of the manufacturing process to ensure defect-free products wastes a lot of resources, time, and money.But there is an effective alternative.Imagine, for example, a welding process where a thermal camera closely tracks the heat signature of the product as it is being manufactured. If the part is being welded incorrectly, an alert goes off immediately so the process can course-correct in real time. Such game-changing efficiencies in manufacturing are beginning to take root, based on advanced technologies like machine learning (ML), and are part of an overarching investment in predictive resolution.<h2>The Evolution of Predictive Maintenance</h2>If the term predictive resolution sounds familiar, it might be because it's closely related to its more familiar cousin: predictive maintenance.The speed with which data-driven technologies have shaped manufacturing in just a few short years is astonishing. Iterations of newer evolutions of digital transformation, like Industry 4.0 and Industry 5.0, have benefited the sector in many ways, especially in facilitating predictive maintenance.Predictive maintenance is one of the primary tenets of Industry 4.0 and runs on the theory that we can use data about equipment health to prevent serious failures before they happen. By studying machines' vibration or heat signatures and inputting this data into ML models, manufacturers can tell when equipment will fail and intervene to avert disaster. Such proactive corrections save expensive downtime, traditionally a significant challenge in the sector.<h2>Moving to Predictive Resolution</h2>Predictive maintenance is a subset of predictive resolution. The same vast suite of advantages that predictive maintenance delivers applies to predictive resolution. But the two are different in a few fundamental ways.Predictive maintenance tells manufacturers when equipment is about to fail. Predictive resolution goes a few steps further and suggests ways to fix the problem. So, while predictive maintenance addresses the&nbsp;ifs and&nbsp;whens, predictive resolution tackles the&nbsp;hows.Predictive maintenance has a much tighter focus, with its sights set on manufacturing equipment. Predictive resolution, on the other hand, covers most business operations—from supply chain management to worker scheduling and process improvements, in addition to equipment health. The welding operation fix using thermal cameras mentioned earlier is an example of predictive resolution addressing process inefficiencies. Machines with real-time monitoring equipment can address production line delays immediately and fix bottlenecks to meet daily and even hourly production quotas.Predictive resolution does not just find what is wrong with manufacturing equipment; it finds—and suggests fixes for—what is not working throughout relevant business operations.<h2>The Technology and Infrastructure Driving the Evolution</h2>Where manufacturing was an opaque process before, digital transformation and data have made&nbsp;<iframe id="66cd9c945347023b21649503" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/analog-devices-max32670-xx-ardz-development-platforms?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> operations more transparent. As a result, it's easier to find and fix inefficiencies.Arguably, one of the biggest game-changers for the industry has been developing and deploying IIoT sensors at scale. When machines have sensors, they can "communicate," and manufacturers can use that information to make data-driven decisions. But IIoT alone is not enough. The sheer glut of data the IIoT generates can easily lead to manufacturers drowning in too much information. However, technologies such as AI help OEMs make sense of the data. When fed into predictive ML models, the data is able to deliver predictive maintenance.Now, the breaking of data silos between various departments in a manufacturing company, along with the ability to read unstructured data, is leading to further advancements in how the industry makes data-driven decisions—through predictive resolution.And the efficiencies have moved beyond machines on the production floor. Generative AI models can train on proprietary information stored in manuals, equipment maintenance logs, emails, and more to create training modules for employees using natural language processing (NLP). Less experienced workers can query generative AI models to access repair instructions and record logs in a central location, so data is not locked and siloed.<h2>The Future Impact of Predictive Resolution</h2>One of the biggest challenges for the manufacturing sector has traditionally been usable and relevant data availability. Now that the technologies are in place, expect predictive resolution to help manufacturers in a variety of new and unique ways.The use cases for predictive resolution abound.Product servitization, for example, where OEMs lease instead of sell equipment, can use predictive resolution for a steadier source of revenue. Manufacturers can access data from this leased equipment to further fine-tune predictive AI models.<h2>Conclusion</h2>Manufacturers are already gaining reduced downtime and cost savings with predictive maintenance. In addition to root cause analysis and predictive maintenance, predictive resolution has a much more sweeping scope in finding and fixing problems beyond machines. OEMs who have paved the way with digital transformation stand poised to reap the benefits from this holistic approach.

Source: William / stock.adobe.com; generated with AI

Manufacturers are already gaining reduced downtime and cost savings with predictive maintenance. In addition to root cause analysis and predictive maintenance, predictive resolution has a much more sweeping scope in finding and fixing problems beyond machines.

Predictive Maintenance vs. Predictive Resolution

But there are times when machinery produces unexpected outcomes, slows down, or stops working altogether. While errors can’t always be avoided, they can be significantly reduced by using the right approach. Many machinery errors are preventable if you develop a strong preventative maintenance strategy to keep everything working just as it should.&nbsp;Preventative maintenance means taking proper care of industrial machinery and equipment to&nbsp;<a title="Downtime" href="https://www.rowse-automation.co.uk/blog/post/how-to-reduce-equipment-downtime" target="_blank">reduce the risk of downtime</a> and minimise the need for costly repairs. This will help to extend the expected lifespan of a piece of equipment. By following a structured and comprehensive preventive maintenance checklist, businesses can ensure that their machinery remains in optimal working condition, leading to sustained operational efficiency and a safer work environment.What follows is a guide to creating a preventive maintenance checklist tailored for industrial machinery. While the full scope of preventive maintenance can be extensive, this guide concentrates on the essential aspects to provide practical and actionable steps that can be applied across different workplaces, environments and industrial equipment.<h2 dir="ltr">What Is Preventive Maintenance?</h2><img data-fr-image-pasted="true" src="https://v3.rowse.co.uk/static/images/blog/posts/xitonuv61bGqCDXV.jpg" alt="Preventive Maintenance Checklist For Industrial Machinery" class="fr-fic fr-dii">Preventive maintenance is all about being proactive. Instead of sitting around and waiting for machinery to break down over time, it involves regular inspections, servicing and repairs to prevent issues before they occur. This proactive approach helps maintain equipment reliability, improve safety and avoid the high costs associated with emergency repairs and unexpected downtime.Reducing costs is critical in today’s economic landscape. With the&nbsp;<a title="Downtime" href="https://uk-manufacturing-online.co.uk/worlds-largest-manufacturers-lose-1-5-trillion-a-year-to-production-outages-as-the-cost-of-failure-soars/" target="_blank">cost of unplanned downtime</a> in industrial environments growing by 50% in just two years, it’s clear that more needs to be done.&nbsp;That ‘more’ is preventative maintenance.&nbsp;This is a strategy that’s often paired with&nbsp;<a title="Predictive Maintenance" href="https://www.rowse.co.uk/blog/post/what-is-predictive-maintenance" target="_blank">predictive maintenance</a>, which estimates when a machine will begin failing by using a system of sensors and data analytics. Preventative maintenance encompasses the tasks needed to stop that failure from occurring.&nbsp;A well-crafted preventive maintenance checklist is an indispensable tool in this process. It provides a clear and consistent guide for maintenance teams to follow, ensuring that all necessary tasks are completed systematically and on schedule, with each machine given the care and attention it needs.&nbsp;<h2 dir="ltr">Essential Elements Of A Preventive Maintenance Checklist</h2>Here are the fundamental components of a powerful checklist:<h3 dir="ltr">1. Inspection Tasks</h3>Regular inspections are the foundation of preventive maintenance. These tasks involve checking the overall status of the equipment, looking for any signs of damage, wear, or tear, and accurately detecting any potential issues before they become bigger problems. Inspection tasks should include:<ul><li dir="ltr">Visual inspection: Look for obvious signs of damage, such as leaks or wear on machinery parts</li><li dir="ltr">Operational inspection: Monitor machinery during operation to detect unusual behaviours</li><li dir="ltr">Safety inspection: Ensure all safety guards, interlocks, and emergency stop buttons are functional</li></ul><h3 dir="ltr">2. Lubrication And Fluid Checks</h3>Lubrication helps to keep moving parts in good working order, reducing friction and preventing excessive wear and overheating. Fluid checks are also essential for systems that rely on hydraulics, cooling or other fluid-based operations. Important maintenance tasks to carry out include:<ul><li dir="ltr">Lubrication: Apply lubricant to bearings, gears, chains and other suitable parts</li><li dir="ltr">Fluid Levels: To maintain proper levels, check and top up hydraulic fluids, coolant and oil</li><li dir="ltr">Leak inspection: Inspect hoses, seals and connections for signs of leaks or wear</li></ul><h3 dir="ltr">3. Mechanical Adjustments</h3>Over time, machinery components may shift or become misaligned, leading to inefficiencies or potential breakdowns. Regular adjustments can help to ensure that the equipment continues to operate to the best of its ability. Manual adjustments that may need to be made include:<ul><li dir="ltr">Alignment: Verify that belts, pulleys and gears are correctly aligned and tensioned</li><li dir="ltr">Tightening: Ensure that all bolts, nuts and screws are tight and secure</li><li dir="ltr">Calibration: Regularly calibrate sensors, gauges and control systems to ensure accurate operation</li></ul><h3 dir="ltr">4. Component Replacement</h3>Some parts of the machinery will undoubtedly wear out and need replacement over time, even with regular maintenance. Identifying and replacing these components before they actively fail is a critical aspect of preventive maintenance. Aspects to consider during this stage of the process include:<ul><li dir="ltr">Wear parts: Replace worn-out belts, filters, seals and gaskets</li><li dir="ltr">Electrical components: Inspect and replace faulty wiring, fuses and circuit breakers</li><li dir="ltr">Critical parts: Replace key components like bearings and valves as per the manufacturer's schedule</li></ul><h3 dir="ltr">5. Cleaning And Housekeeping</h3>When machinery is clean, it becomes easier to inspect and, therefore, easy to spot any potential issues. Cleaning equipment regularly can help to keep dirt, dust and other contaminants at bay, reducing the risk of damage that can ultimately impact efficiency. Cleaning tasks should include:<ul><li dir="ltr">Surface cleaning: Wipe down machine surfaces to remove dust, grease and other contaminants</li><li dir="ltr">Internal cleaning: Clean or replace air filters, fans and other internal components</li><li dir="ltr">Work area maintenance: Keep the surrounding area clean and free of obstructions</li></ul><h3 dir="ltr">6. Testing And Verification</h3>Perhaps the most overlooked aspect of preventative maintenance is testing and verification. After completing maintenance tasks, testing the equipment can provide much-needed confidence that the machinery is working properly and that the maintenance has been effective. This stage includes:<ul><li dir="ltr">Operational testing: Run the machine through standard operations to confirm it works as expected</li><li dir="ltr">Safety checks: Test emergency stop functions, safety interlocks, alarms and other safety features</li><li dir="ltr">System monitoring: Use diagnostic tools to monitor performance and identify lingering issues</li></ul><h2>&nbsp;Creating A Customised Preventive Maintenance Plan</h2>While the above checklist provides a general framework, every business should be able to tailor their preventive maintenance plan to the specific needs of its own facility and equipment.&nbsp;Here are four steps to customise a maintenance plan:<ol><li>Identify all equipment: Create an inventory of all machinery that requires maintenance</li><li>Determine maintenance frequency: Make a note of how often each machine requires attention</li><li>Delegate tasks: Make a schedule that shows who is in charge of which task – and when</li><li>Implement and monitor: Once your checklist is in place, integrate it into your daily operations</li></ol><h2 dir="ltr">Achieving Long-Term Success With Preventive Maintenance</h2>A robust preventive maintenance checklist is not just a tool for maintaining industrial machinery. It's a critical component of a successful long-term maintenance strategy that drives efficiency, safety, and cost-effectiveness. By regularly inspecting, servicing and repairing equipment, businesses can prevent costly breakdowns, extend the lifespan of machinery and maintain a safe environment.Preventative maintenance strategies can be powerful, but to ensure they deliver results, it's essential to keep your checklist up to date, customise it to your specific needs and ensure that all maintenance tasks are performed consistently and thoroughly. With a proactive approach and a commitment to regular maintenance, you’ll be giving yourself exactly what you need to keep your industrial machinery in top condition, supporting the long-term success of your operations.

In modern industry, it’s critical that machinery continues to operate efficiently and effectively whenever needed. That is the key to maintaining optimal productivity and ensuring safety.

Preventive Maintenance Checklist For Industrial Machinery

Continual advancements in space technology are reshaping our capacity to manage Earth's affairs with precision and efficiency. Amidst the complexities of urbanization, climate change, and global connectivity, the need for sophisticated infrastructure has become increasingly apparent.&nbsp;Satellites, with advanced functionalities, have emerged as indispensable tools for data acquisition, analysis, and communication, which are crucial for informed decision-making on Earth.With their high-resolution cameras, multispectral sensors, and robust communication capabilities, we can capture and transmit data from a wide range of Earth-related activities, from urban planning and disaster management to agricultural monitoring and environmental protection.By continuously orbiting the Earth, satellites capture detailed images and other sensor data covering the whole planet’s surface. We can use this data to track changes in landscapes, monitor weather patterns, and observe natural disasters like forest fires, floods, and hurricanes in real time.This data is collected and transmitted back to Earth, where it can undergo rigorous analysis. Machine learning algorithms, data analytics, and other advanced computing techniques allow us to interpret the data with ease. For example, predictive modeling is utilized to forecast weather changes or track the migration patterns of endangered species. The ability to process real-time data enables quick decision-making, which is especially crucial during responses to natural disasters and emergencies.&nbsp;Communication is another critical functionality of satellites. They ensure communication lines are able to remain open, even in the most remote parts of the world. This facilitates global connectivity, allowing data, voice, and video communication to be transmitted across diverse geographical landscapes.<h1 dir="ltr">Maintenance in space</h1>On Earth, if something breaks down in a factory or a power plant, we don’t build a replacement. Instead, we send a repair team with spare parts, and even better yet, we monitor the components' wear and replace them before they break down. This preventive maintenance approach minimizes downtime and reduces the costs associated with sudden breakdowns.This methodology is critical in industries where reliability and uptime are essential. By continuously monitoring equipment health through sensors and predictive analytics, we can identify potential problems before they lead to operational failures. However, this approach faces unique challenges in space, where sending a repair team is not feasible due to the vast distances and extreme conditions.The transition from Earth-based maintenance to space requires innovative solutions to overcome these challenges. The harsh space environment, including vacuum conditions, microgravity, and cosmic radiation, makes traditional maintenance methods impractical. Additionally, the delay in communication between Earth and spacecraft further complicates real-time interventions, necessitating a more autonomous approach to maintenance and repair operations in space.<a href="https://www.ant61.com/" target="_blank" rel="noopener noreferrer">ANT61&nbsp;</a>develops autonomous robots that enable the maintenance of satellites without the need to put human lives at risk. ANT61 is providing solutions for both: their Beacon product allows satellite operators to understand what went wrong with their satellites and restore them back to operation.For larger and more expensive satellites, they are building robots that will dock, refuel, and, in the future, refurbish satellites, prolonging their useful life. At the core of these robots lies ANT61 BrainTM, the innovative devices that combine machine vision and decision-making technology, enabling the autonomy of these maintenance robots. Autonomy is very important as, due to the speed of light limitations, it won’t be possible to control every movement of these robots remotely from Earth.<h3 dir="ltr">BrainChip AkidaTM&nbsp;: A revolutionary neuromorphic processor for edge AI applications</h3>The first generation of the ANT61 Brain uses the <a href="https://brainchip.com/akida-neural-processor-soc/" target="_blank" rel="noopener noreferrer">BrainChip AkidaTM</a> chip for power-efficient AI and is currently on board the Optimus-1 satellite, which was deployed recently by the SpaceX Transporter-10 mission. ANT61 will test the ANT61 Brain later this year and perform training and evaluation of various neural networks that we will use for future in-orbit servicing technology demonstrations.The BrainChip Akida™ chip is a groundbreaking advancement in neuromorphic computing, designed to mimic the neural architecture of the human brain. This technology stands out for its ability to process data directly at the point of acquisition, greatly enhancing efficiency by reducing the reliance on distant cloud-based systems for data processing.Akida's unique capability lies in its event-based neural processor, which processes data only when needed, using data sparsity to significantly reduce the number of operations required. This leads to lower power consumption and heat dissipation, making it highly suitable for the demanding conditions of space. Each Akida node consists of four Neural Network Layer Engines (NPEs), which can be configured for various functions, such as convolutional layers or fully connected layers, and support incremental learning and high-speed inference. This configuration flexibility allows the chip to efficiently handle a wide range of AI tasks without needing constant connectivity or high power draw.Akida's scalable architecture enables the chip to support up to 256 nodes in a mesh network, boosting computational power while maintaining a small footprint. This scalability is crucial for space applications where efficiency and performance are vital. The entire neural network can be embedded directly within the Akida fabric, eliminating the need for frequent data transfers that consume significant power and reduce system responsiveness.Another key feature of the Akida chip is its on-chip learning capability, which allows it to adapt and improve its performance over time without external intervention. This feature is particularly beneficial in space, where conditions can change rapidly and autonomy is crucial. By processing and learning from data locally, Akida enhances the autonomy of satellite maintenance robots like those developed by ANT61, enabling them to perform complex tasks with minimal latency and enhanced reliability.The ANT61 team chose to partner with BrainChip because they believe that neuromorphic technology will bring the same exponential improvement in AI as 20 years ago. The shift from CPU to GPU opened doors to deep neural network applications, which are at the core of all AI technologies today. Neuromorphic technology is also perfect for space: the lower power consumption means less heat dissipation, and we can get up to five times more computational power for the same electrical power budget.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1715339791069-Akida_1000_chip-1.jpg" style="width: 100%px;" class="fr-fic fr-dib">Akida AKD1000 is a reference chip implemented with TSMC at 28nm<h1 dir="ltr">The ANT61 vision for the future</h1>Humanity’s expansion to the cosmos requires infrastructure that can only be built by robots. With its in-orbit servicing experience, ANT61 aims to become the main supplier of the robotic workforce for Moon and Mars installations. This will enable companies from Earth to project their ambition to space, providing valuable services and resources for future off-world factories and cities.Neuromorphic computing, exemplified by technologies like the BrainChip Akida™ chip, is set to play a pivotal role in this spacefaring era. This form of computing brings several advantages crucial for space applications, such as low power consumption, high efficiency, and the ability to perform complex computations needed for autonomy. By mimicking the human brain, neuromorphic processors can process large volumes of sensor data efficiently, making real-time decisions without the need to send data back to Earth for processing.The integration of neuromorphic computing into space robotics promises to significantly improve these machines' capabilities. Robots equipped with advanced AI processors can better handle the unpredictable nature of space environments, adapting to new challenges autonomously and performing tasks ranging from construction to maintenance and repair. This capability ensures that space habitats are built efficiently and can be sustained with minimal human oversight.ANT61's vision of utilizing these technologies to support human expansion into space reflects a forward-thinking approach that will not only facilitate the construction of off-world establishments but also ensure their long-term sustainability and success.&nbsp;

Remote satellite maintenance is crucial to critical data acquisition and global communication


Advancing Earth Management Through Neuromorphic Computing Powered Satellites

The globalization of supply chains is being formed on production lines that are able to supply only the required quantity of products at the time required. This means that an obstacle arising in one place in the production line may strike a major blow to the entire supply chain.The causes of production delays and stoppages include conflicts, disasters, raw material shortages, and equipment and device failures. In particular, production stoppages and the outflow of defective products due to equipment and device failures may lead to major problems for manufacturers. These problems include the expense required to recover those defective products and opportunity losses due to product supply stoppages. Therefore, equipment maintenance, which bears responsibility for the stable operation of the production line, is an important issue that holds the key to the life of manufacturers.The importance of equipment maintenance has been strongly expressed up to now. The techniques of equipment maintenance have also been advancing from breakdown maintenance to preventive maintenance and then onto predictive maintenance as well in recent years.We introduce in an easy-to-understand manner equipment maintenance that is continuing to evolve in this way—from basic knowledge such as the types of equipment maintenance and their advantages and disadvantages to the technologies to realize the predictive maintenance that is considered the ideal form of equipment maintenance.<h2>What Is Equipment Maintenance?</h2>Equipment maintenance refers to the activities to keep various production equipment in factories functioning normally. It is also called “machine maintenance.” The purposes of equipment maintenance are cited as being, for example, to prolong the life of machine components used in equipment, to shorten machine and device downtime, and to prevent unexpected failures in addition to repairing equipment that has failed.Moreover, equipment maintenance up to now has mainly focused on machines and devices. Now, the focus is also on the software that controls the Programmable Logic Controllers (PLCs) and machines and devices with the conversion of regular factories into smart factories using industrial robots, machine vision, and other technologies.There are other terms similar to maintenance such as “upkeep” and “care,” but these are the same as equipment maintenance. The reason is that they all involve inspecting equipment and then servicing or repairing it as necessary so that it does not fail.<h2>Types of Equipment Maintenance and Their Advantages and Disadvantages</h2>Equipment maintenance includes breakdown maintenance and preventive maintenance. Preventive maintenance is further broken down into time-based maintenance and condition-based maintenance (Figure 1). We explain here the features and the advantages and disadvantages of each type.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985901545-predictive-maintenance-img0001_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 1: Types of Equipment Maintenance<h3 id="isPasted">What Is Breakdown Maintenance?</h3>This is maintenance that is performed after a piece of equipment’s functions have declined or after it has stopped functioning (Fig. 2).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985917150-predictive-maintenance-img0002_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 2: Breakdown MaintenanceAdvantages: The advantages of breakdown maintenance include the fact that the burden on maintenance work is low because the condition of the equipment is not checked until it fails or a malfunction is discovered. Another advantage is that it keeps the costs involved in maintenance low in the case of minor failures. Disadvantages: Failures and malfunctions occur unexpectedly. Therefore, there may be delays in obtaining repair components, and so it may take some time to carry out repairs. In addition, there are risks such as major disruptions to production plans if the failure or malfunction occurs in a core piece of equipment. Furthermore, if there is a delay in discovering the failure or malfunction in the equipment, it may lead to defective products and their flowing out of the factory. Dealing with such issues may require a considerable amount of expense and time.<h3>What is Preventive Maintenance?</h3>This is maintenance that is performed based on a piece of equipment’s service life, the number of times it is used, its condition, or other factors. It is also called “time-based maintenance” (Fig. 3).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985934940-predictive-maintenance-img0003_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 3: Preventive MaintenanceAdvantages: The maintenance work is performed once a certain period has been reached. Therefore, it is possible to prevent failures and malfunctions from occurring in equipment. It is an effective maintenance method when the service life of each component used in equipment or the number of times those components are used can be grasped accurately. Disadvantages: It is necessary to establish criteria to ascertain as accurately as possible the life of components. Maintenance may be performed after a failure if the criteria is not accurate. Conversely, component and time losses may arise such as from the replacement of components that can still be used.<h3>What Is Predictive Maintenance?</h3>This is maintenance that is performed in line with extent of a piece of equipment’s deterioration by constantly monitoring its condition. It is also called “condition-based maintenance” (Fig. 4).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985956264-predictive-maintenance-img0004_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 4: Predictive MaintenanceAdvantages: The maintenance work is performed when the equipment deteriorates. Therefore, it is possible to reduce component and time losses such as from the periodic stoppage of equipment for maintenance and the replacement of components that can still be used. Of course, it is also possible to prevent failures and malfunctions that would lead to the equipment stopping unexpectedly. Disadvantages: It is essential to have equipment to constantly monitor the condition of equipment and to store the collected data. Specifically, the constant monitoring of equipment requires a large number of various types of sensors. In addition, data loggers and similar recording devices are needed to store data. Furthermore, it is necessary to have equipment and other technologies to connect to those recording devices to communicate the data.<h2>Four Technologies to Turn Preventive Maintenance into Predictive Maintenance</h2>The most common method of maintenance currently is preventive maintenance whereby equipment is periodically maintained by determining the inspection timing based on the service life of each component used in equipment or the number of times those components can be used. Furthermore, there are an increasing number of cases in which semi-predictive maintenance is being adopted. This is when a large number of sensors that measure vibrations, temperature, current, voltage, and other elements are attached to equipment and thresholds are then set for each of them with maintenance being performed when those upper or lower limits are exceeded. In fact, a survey conducted on companies engaged in converting regular factories into smart factories produced results showing that over 96% of them cited “equipment maintenance utilizing sensors and AI” as the reason they are continuing to convert their factories into smart factories (Fig. 5).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714985974057-predictive-maintenance-img0005_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 5: Reasons Why Companies Want to Continue Converting Regular Factories into Smart Factories* About the survey:&nbsp; Surveying entity: Murata Manufacturing Co., Ltd. Survey focus: 11,084 workers in the manufacturing industry in Japan (screening survey) / 500 workers in the manufacturing industry involved in converting their company’s regular factories into smart factories (main survey) Survey method: Internet survey Survey period: 3 days from January 25 (Wed.) to 27 (Fri.), 2023 * The total values may not necessarily match due to rounding.In this way, equipment maintenance is currently undergoing a switch from preventive maintenance to predictive maintenance. We explain here the four technologies that can help with this switch from preventive maintenance to predictive maintenance.<h3>1. Introduction of Sensors into Equipment Maintenance</h3>Predictive maintenance begins with constant monitoring of the condition of equipment. There are individual differences in judgment when this monitoring is performed with the eyes and touch of people. This means it is not possible to respond accurately. We can quantify the condition of equipment by introducing sensors. Visualizing and analyzing the data collected from those sensors then enables us to respond more accurately. However, this requires installing many types and a large number of sensors in large factories. Accordingly, routing and connecting the sensor wiring requires many man-hours when changing the setup. Therefore, it is best to have noise-resistant sensors capable of wireless communication with a long transmission distance.Moreover, devices have been developed that can keep a log of the actions taken by workers on manufacturing lines in recent years. It is also possible to record how those workers respond when trouble occurs. Utilizing these records allows various matters to be saved as data, including the deterioration of equipment that occurs on the manufacturing line and the actions taken by workers in response. This data can be used to give hints to improving processes in addition to maintenance.<h3>2. Visualization of the Condition of Complex Equipment: Sensor Fusion</h3>Sensor fusion is a technology that realizes cognitive functions that cannot be obtained with a single sensor on an engineering basis. Specifically, sensor fusion has already been introduced into Advanced Driving Assistant Systems (ADAS). For instance, examples include reading the shapes of people, obstacles, and other objects with an image sensor and temperature sensor and then measuring the distance with a radar sensor utilizing milliwaves and microwaves to grasp the situation in the direction in which those objects are moving. It has also become possible to display warning messages on monitors in vehicles and to apply brakes automatically. This utilizes sensor fusion as a technology to, for example, automatically determine the situation with data collected from multiple sensors such as image sensors and radars and to then convey those results to the driver. When we use this technology in equipment maintenance, we can analyze the measurement data from vibration sensors, temperature sensors, current sensors, and voltage sensors on an integrated basis. For example, if a current or voltage value is abnormal despite the motor vibrations and temperature being normal, we can determine that there has been a problematic change to the load on the part where the motor is operating. In addition, if an abnormal value is seen only in a vibration sensor, it is likely to be bearing wear, shaft deformation, level abnormality, or similar (Fig. 6).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714986016706-predictive-maintenance-img0006_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 6: Introduction of Sensor Fusion into Equipment MaintenanceConventionally, such abnormalities were grasped and determined by workers reading each sensor value and then comparing those values with their past experiences.&nbsp; However, if we use the technology of sensor fusion, we can aggregate data collected by many sensors and display it on monitors or other devices as results that indicate the condition of equipment. This allows even inexperienced workers to accurately grasp the condition of equipment.<h3>3. Introduction of AI into Equipment Maintenance</h3>Sensor fusion is an outstanding technology. However, as the number of sensors increases and measurements become more precise, the amount of data increases. This leads to calculations becoming complex. It also becomes difficult to output data that indicates accurate results. Accordingly, the introduction of deep learning into equipment maintenance has come to be seen as important. Introducing the AI technology of deep learning into equipment maintenance enables data collected from multiple sensors to be integrated and analyzed by AI. If there is an error in the output results, it is corrected through machine learning. Furthermore, accurate results are produced. When we utilize AI in equipment maintenance, we become able to respond correctly to the condition of equipment that is constantly changing with self-learning such as by comparing the data collected during normal times and data collected from sensors to extract the difference in addition to simply detecting abnormalities that are determined by establishing a threshold (Fig. 7).<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714986035251-predictive-maintenance-img0007_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 7: Introduction of AI into Equipment MaintenanceIn this way, introducing AI into equipment maintenance doesn’t just reduce the differences in judgments due to differences in the proficiency level of the workers; we can also solve issues in conventional maintenance activities that rely on manpower, which involves investing a lot of personnel and hours in work, including monitoring and inspections.&nbsp;<h3>4. Introduction of Edge AI Cameras and Other Edge AI Devices</h3>Edge AI is a technology that applies edge computing to AI. In edge AI, AI processing is performed with various sensors, cameras, mobile terminals, and other edge devices at the end of networks (Fig. 8). On the other hand, in contrast to edge AI, there is a technology called “cloud AI.” This is a technology that applies cloud computing to AI. This means AI processing is performed on the cloud server connected to the network and the results are then returned to the edge devices. If we compare edge AI and cloud AI, we find that there are advantages to edge AI. These advantages include outstanding response speed and data confidentiality because the AI processing is performed on edge devices without involving a network. This also means edge AI is not impacted by the quality of the network. High data confidentiality is an absolute requirement especially for equipment maintenance that handles data in factories. Moreover, a high response speed is sought in vibration and acceleration calculations, which require data collection at high sampling cycles. Therefore, we can say that edge AI is an attractive technology for predictive maintenance involving the handling of large volumes of data.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714986052981-predictive-maintenance-img0008_en.png" style="width: 100%px;" class="fr-fic fr-dib">Fig. 8: Introduction to Edge AI DevicesHowever, edge devices equipped with edge AI are small. This means they have disadvantages such as inferior memory size and calculating capacity compared to cloud AI. Accordingly, it is necessary to select either cloud AI, edge AI, or to use both together according to your purpose.<h2>Summary</h2>The importance of equipment maintenance for the stable operation of manufacturing lines has long been recognized. Nevertheless, on the other hand, it is also true that too much emphasis on production has led to daily maintenance activities being neglected. Nowadays, with the globalization of manufacturing having long since progressed, manufacturing lines are continuing to constantly supply products to supply chains. In particular, supply chain management has been built based on production output during normal operations in regular factories that are being converted into smart factories. Under these circumstances, unexpected equipment failures on the manufacturing line can deal a major blow to the supply chain and cause damage to a company’s image. Moreover, the introduction of sensor fusion, AI, and other technologies into equipment management is not just about optimizing equipment maintenance, reducing personnel expenses, and solving labor shortages. It is a cutting-edge approach with many advantages including the continuing maintenance of high productivity, the optimization of energy usage, and the effective utilization of personnel. It is no exaggeration to say that realizing predictive maintenance by introducing sensor fusion, AI, and other technologies into equipment maintenance is the key to future corporate management for the manufacturing industry, which is surrounded by a complex economic environment such as the widening of supply chains.&nbsp;<hr><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1714986081243-1714986081243.png" class="fr-fic fr-dii">If you have any questions based on this article that you would like to discuss with an expert at Murata, don't hesitate to reach out. There's an entire team ready to support you with your question.<a href="https://www.murata.com/en-eu/contactform?&Detail=Wevolver%20request" target="_blank" rel="nofollow" class="button-main-action">GET IN TOUCH</a>

The importance of equipment maintenance is clear. In recent years, equipment maintenance techniques have also advanced from breakdown maintenance to preventive maintenance and now focus on predictive maintenance.

The Technology That Realizes Predictive Maintenance

Explore the transformative impact of predictive maintenance in industrial automation. Discover how Infineon’s advanced predictive maintenance solution enables operational efficiency, reduces downtime, and fosters sustainable industrial growth through innovative edge-to-cloud integration.
