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Gas Pipeline Improves Station Efficiency and Drives Revenue with DataRPM -  Industrial IoT Case Study
Gas Pipeline Improves Station Efficiency and Drives Revenue with DataRPM
In the capital-intensive oil and gas industry, businesses rely heavily on expensive assets that are deployed in harsh environmental conditions. From a drilling point in the sea to an intermediate station in the desert, the dynamic environmental conditions at each point along the long line affect the performance of the assets deployed along the line. The systems that are used to support these mission-critical assets must also be highly reliable, responsive and secure.One company that operated a long-distance gas pipeline encountered numerous challenges with the overall efficiency of its pipeline, ranging from sub-optimal usage to wastage of natural resources. Even with the optimal equipment and setup, the wide array of variables in operating conditions combined with the sheer distance covered by the pipeline made running the business difficult.In this case, there were 22 injection stations along the length of the pipeline, operating under very disparate conditions with different efficiencies. This made it difficult to identify the interdependent effectiveness of these injection stations, despite having a large data set on various parameters at each injection substation. Even a single instance of failure could cost the company hundreds of thousands of dollars in lost revenue as well as any additional costs for repairs that had to be made.The company was spending $5 million per mile of pipeline annually in corrective maintenance. Along with this, the loss of revenue due to the undelivered material was estimated at $250 million. With energy prices dropping, the loss in revenue directly reduced the bottom line of the company. With the clock ticking and revenue dipping, building a perfect efficiency improvement model became a top priority.
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FOUP Nitrogen Filling Machine Monitoring Management Application - SUNIX Industrial IoT Case Study
FOUP Nitrogen Filling Machine Monitoring Management Application
| BackgroundThis customer is specialized in the development of ultra clean gas filling system technology for semiconductor wafer manufacturing.  They require monitoring system to control the nitrogen pressure level of the FOUP machine.  Their current system configuration is complicated to setup as it requires IP setting to connect FOUP serial server devices, which needs additional personnel to constantly monitoring the system.  They are seeking for new system design to help improve the overall manufacturing facility efficiency, and pursuing higher product quality control. | Challenges We Are FacingIP configuration and management of multiple connectionsHigh cost of deployment and maintenanceComplete system shutdown for maintenance will affect production output
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CN Helped Pine Printshop with a Responsive and Top-notch E-commerce Portal - Capital Numbers Infotech Pvt Ltd. Industrial IoT Case Study
CN Helped Pine Printshop with a Responsive and Top-notch E-commerce Portal
To digitally expand their business, Pine Printshop was looking for a catalog-based site that would help people buy ready-made products (e.g. apparels, board pins, stickers, etc.) and even allow customers to personalize their own t-shirts, caps, and hoodies.
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Smart Ccondition Monitoring Saves USD 30 Thousand In A Forging Unit - Infinite Uptime Industrial IoT Case Study
Smart Ccondition Monitoring Saves USD 30 Thousand In A Forging Unit
The 1000 Ton main forging press had a 75 HP motor and fed a trimming machine. The motor pulley combination was situated on top of the Press at a height of about 15 feet thereby reducing its access for routine maintenance. The company found difficulty ensuring constant uptime of the Press.
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Ensuring the safety of Alzheimer’s and dementia patients through IoT-driven trac - Ingram Micro Industrial IoT Case Study
Ensuring the safety of Alzheimer’s and dementia patients through IoT-driven trac
Wandering is a common symptom of Alzheimer’s and dementia even at the early stages (60% of Alzheimer’s patients will wander off and become lost at some point). These diseases kill brain cells and destroy people’s memories, most notably short-term recall. Patients forget the last thing they did, so their first impulse is to stand and start moving with the intention of doing something. This is compounded by the fact that individuals with dementia are easily disoriented and become confused in crowded or unknown situations, and they have a strong tendency to want to escape.
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4G Power Status Monitoring Alarm Used in Chicken Farm
养鸡场使用的4G电源状态监视警报基于4G无线网络通信,用于养鸡场以监控电源故障,缺相,温度,湿度并现场驱动频闪警报器。
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USD 1.2 Million Saved On A Forging Press Line By Predicting Cutter Life - Infinite Uptime Industrial IoT Case Study
USD 1.2 Million Saved On A Forging Press Line By Predicting Cutter Life
The major press line in the company has a circular saw machine which cuts metal rods with precision in predefined lengths for further heating in the furnace. The cut pieces are then fed to the forging line to make automotive components. The length and perpendicularity of the cut pieces are crucial to obtain a good quality forging.It was observed that circular saw failed to maintain the precise length and perpendicularity while cutting the metal rods leading to heavy rejections. This was a serious concern and routine preventive maintenance was unable to overcome it.
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Leveraging AI to Upgrade Product Quality Management in Speed and Accuracy - IBM Industrial IoT Case Study
Leveraging AI to Upgrade Product Quality Management in Speed and Accuracy
IBM
To succeed in the fiercely competitive LCD manufacturing industry, CSOT must deliver high-quality products within a tight time frame, but time-consuming product inspections have hampered its agility. Quality inspectors had to inspect each LCD screen individually to check for flaws. This takes quite a bit of time.
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Modular AI Defect Inspection Solution - Advantech Industrial IoT Case Study
Modular AI Defect Inspection Solution
Smasoft Technology Co., Ltd. is a System Integrator that develops industrial automation software and offers AI application solutions. Its self-developed AINavi-AOI-Seq automated software platform and AINavi-AOI-Semicon AI defect inspection tool have been well-liked and adopted by the semiconductor and electronics industries. Recently, the company was commissioned by a semiconductor equipment manufacturer that manufactures Extreme Ultraviolet Light (EUV) pod inspection machines to implement defect AI inspection features.The EUV pod inspection machines have built-in AOI software, but can only find defective products, not determine what is causing the issue in the manufacturing process. To make products more useful, the semiconductor equipment manufacturer decided to upgrade their EUV pod inspection machines with AI features.According to the customer's request, Smasoft's AI solution must complete the analysis of 380 images for a single pod within two minutes and inspect different materials at the same time. Consequently, multiple sets of AI models (algorithms) were needed for interpretation. In addition, because the solution needed to be installed in a cabinet in the lower half of the machines, the size and configuration of the hardware had to be constrained due to the limited space.To this end, Smasoft would implement two sets of software, AINavi-AOI-Seq, and AINavi-AOI-Semicon, to distinguish the types and locations of defects through AI, and then classify defects by threshold screening. Moreover, the results would be exported into a test report to facilitate identifying the source of the problem.To meet these software requirements, Smasoft needed to purchase a hardware solution with strong computing performance and stable operation. The solution needed to be compact in size and flexible in configuration to overcome physical space constraints.
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Edge Solutions for Smart Monitoring of HVAC Manufacturing - Advantech Industrial IoT Case Study
Edge Solutions for Smart Monitoring of HVAC Manufacturing
This project involved conceptualizing a smart monitoring and management solution for Daikin India, a subsidiary of Daikin Industries Ltd. and a leading HVAC solutions provider in India. More specifically, Daikin India produces a wide range of energy-efficient air conditioning systems for residential, commercial, and industrial buildings.In order to optimize energy efficiency and productivity at its factories, Daikin India wanted to implement an equipment monitoring and data collection solution. However, because the HVAC subassembly lines featured numerous programmable logic controllers (PLCs), the available installation space and network capabilities were limited. Therefore, the company needed a compact yet versatile solution for acquiring and visualizing production data without high networking/infrastructure costs. Moreover, to facilitate equipment monitoring and operational optimization, Daikin India needed a system with the following capabilities/specifications:Supports smart real-time monitoring of HVAC subassembly linesEnables seamless acquisition and visualization of equipment dataMinimizes and streamlines data transmissionsConfigurable PLC I/O data collection flexibilityReliable industrial-grade hardware
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Smart Factory Solutions for Tobacco Industries - Advantech Industrial IoT Case Study
Smart Factory Solutions for Tobacco Industries
British American Tobacco (BAT), a British multinational company that manufactures and sells cigarettes, tobacco, and other nicotine products, required a factory solution to automate its product control processes. From the transportation of the tobacco and cigarette paper to the placement on the cigarette machines to the packing conveyor, the process needed to be significantly automated to significantly meet quality control targets for the final product.They also required support for the continuous use of legacy equipment, such as relay-controlled cigarette machines dating back to the 90s and AMK servo drive systems, to sustain production levels at speeds of 8000 to 16000 pieces per minute. In short, it is a production target impossible without improved and precise quality measures at every stage of production. Furthermore, labeling requirements meant flexibility had to be incorporated for BAT to meet changing regulatory guidelines.
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Smart Monitoring Solutions for Solar Panels - Advantech Industrial IoT Case Study
Smart Monitoring Solutions for Solar Panels
For this project, NWC partnered with a client that generates and sells electricity serving residential, commercial, and industrial customers. The requirement to monitor the amount of electricity produced by 88,000 solar panels with a power generation capacity of 28 MW/h in a field size of 700 x 700 meters challenged the customer. The initial idea was a 13-kilometer wired optical network; over 1 billion yen cost defined the approach as expensive and impractical. Therefore, the client needed a wireless gateway solution to communicate between the site and the monitoring center.The project focused on designing a solar power monitoring system to meet the following conditions:Cost-effectivenessDurabilityWireless communicationFlexible Data acquisition (IOs and PLCs)
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Smart Monitoring System for Taiwan's First Micro-Biomass Power Plant - Advantech Industrial IoT Case Study
Smart Monitoring System for Taiwan's First Micro-Biomass Power Plant
Sunforce was asked to develop a monitoring system for micro biomass power plants to reduce labor expenses and equipment failure rates while increasing power generation. They also wanted to perform scheduling and cascade control to create standard operating procedures to achieve remote monitoring and real-time management. In the future, they will combine artificial intelligence with gradually accumulated operational data to perform intelligent monitoring.
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Endian Technology Helps to Support Hera Group to Provide Utilities & Services - Endian Industrial IoT Case Study
Endian Technology Helps to Support Hera Group to Provide Utilities & Services
Hera is now among the nation’s largest multi-utilities, born in 2002 out of the aggregation of 11 municipal companies operating in Emilia-Romagna, Italy. The first corporation of its kind nationwide, Hera worsks mainly in the environment (waste management), water (aquaduct, sewage and purification) and energy (electricity, gas distribution and sales, energy services) sectors. Other services offered include public lighting and telecommunications. Its range of activities undergoes continuous and constant development, and meet the needs of 4.4 million citizens in over 350 municipalities in Emilia-Romagna, Friuli-Venezia Giulia, Marche, Tuscany and Veneto. Right at the technological heart of HERA is HERAtech, the company that manages the work requested by customers for all network services managed by the Hera Group and also handles the design and construction of plants and networks in addition to highly specialised technical activities, such as plant remote control, the technical call centre that manages Emergency Services and the Analysis Laboratories for drinking water, wastewater and waste.The project by Endian for Hera is developed in cooperation with the Fluids Remote Control Division and its main goals are to fully manage the suppliers’ access to plants and devices, and to punctually monitor the network distributed over the regions covered by the service. Control activity takes action in multiple data centers, the places where all critical infrastructure is housed, and it’s all about authorizing access to suppliers and scanning all connections to detect any possible unauthorized devices or intrusions. 
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Predictive Maintenance for Industry 4.0 - Microchip Technology Industrial IoT Case Study
Predictive Maintenance for Industry 4.0
Industrial robotic systems see increasing levels of vibration on their mechanical elements which often indicates the need for service. Factory operations personnel need to find a way to increase their awareness of vibration and use AI/ML analytics to interpret the data and address the issue in a timely manner. This is a fairly standard interpretation of predictive maintenance that many Industry 4.0 advocates aspire to.In the past, service schedules were accommodated using a paper log file, and the intervals between were often decided arbitrarily by a supervisor based on their experience and feel for the operation. As robotic systems in modern manufacturing become more complex, factory managers need to be aware of their maintenance requirements in real-time and be on top of both routine and critical service scheduling in order to avoid an interruption in service.
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Catsbill invoice generator -  Industrial IoT Case Study
Catsbill invoice generator
Whether big or small, a Digital shift is always difficult to carry out. We aimed for a digital transformation thus increasing the internal operational efficiencies by introducing self-service and automation, and improving the client experience. Moreover, the utmost challenge was to carefully Validate the single-digit precision of results by rounding off the numbers in calculations for efficiency and accuracy.In the end, Sifars was looking for a reliable way to register customer data securely while naturally engaging them for their daily tasks.
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Mahindra World City - Xenius Industrial IoT Case Study
Mahindra World City
The challange was to build first smart city in India?
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Artificial Intelligence Ensures Efficient Maintenance  - Dell Technologies Industrial IoT Case Study
Artificial Intelligence Ensures Efficient Maintenance
The motto of the automotive industry is: Time is money. Machine downtime must be prevented to avoid costly production outages. The EDAG Group had been commissioned to implement predictive maintenance for a customer, requiring a combination of intelligent software and high-performance hardware.
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Partnering with Community Health Systems to Implement a COVID-19 Tracking Soluti - kajeet Industrial IoT Case Study
Partnering with Community Health Systems to Implement a COVID-19 Tracking Soluti
Detecting and containing infection clusters and controlling community transmission is vital to alleviating the impact of the COVID-19 pandemic on human health. Isolating affected populations and restricting social interaction, travel, and the intermixing of people have long been used as remedies to the spread of contagious illnesses. Today, local, state, and federal initiatives are using similar approaches with cutting edge technology to gather and share data and decrease the toll of COVID-19. Public health officials need quick and accurate information to identify cases and they control transmission using strong, clear, and effective communications.
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Ensuring the safety and security of the pharmaceutical supply chain with IoT shi - Ingram Micro Industrial IoT Case Study
Ensuring the safety and security of the pharmaceutical supply chain with IoT shi
The company was looking to cover all transportation legs of the supply chain: • The transport of partially completed pharmaceutical products from manufacturing facilities to processing centers • The shipment of finished products to regional warehouses • The delivery of the finished products to local distributors Although pilferage, hijacking and product tampering were ongoing problems, the containers couldn’t be sealed because the cargo had to be accessible for random checking at government checkpoints.
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Ensuring Safe Jam-making for Delicious Results - Nikon Industrial IoT Case Study
Ensuring Safe Jam-making for Delicious Results
In jam and fruit spread manufacturing, there is a process to eliminate foreign objects and impurities contained in the materials. Until now, that inspection has been conducted by human eyes, however, there were several issues such as the heavy physical burden on employees and inconsistent detection accuracy. Due to the wide variety of raw materials and differing shapes of fruits, it was considered extremely difficult to automate this inspection process.
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Reducing Scrap and Increasing Efficiency in Brick Production - Craftworks Industrial IoT Case Study
Reducing Scrap and Increasing Efficiency in Brick Production
Quality management in this facility was only done at the end of the production process. This makes it hard to link scrap output to its root causes and understand when and why faulty bricks are being produced. This makes the process not only unpredictable but also inefficient.
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Intelligent Visual Detection of Contaminants - Axora Industrial IoT Case Study
Intelligent Visual Detection of Contaminants
Contaminants on conveyor, if not detected, can lead to an increased cost and machine downtime.
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Electric Vehicle Solutions Guide - COGNEX Industrial IoT Case Study
Electric Vehicle Solutions Guide
Low quality of human inspection in EV manufacturing
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5G+AI: Intelligent Sorting of Items in the Production Process  - Huawei Industrial IoT Case Study
5G+AI: Intelligent Sorting of Items in the Production Process
In many industries such as industrial manufacturing and logistics, there are many needs for identifying, detecting and classifying products or objects. Traditional detection methods based on artificial vision are prone to fatigue, and cannot always guarantee high detection efficiency, and due to the physiological limit of the human eye itself, it is difficult to achieve high standards in terms of speed and accuracy. Therefore, the traditional manual detection method restricts the development and improvement of the productivity level and has been difficult to meet the needs of production. More and more sorting robots based on machine vision are widely used in various industrial production lines. That is, the target image information is obtained through the industrial camera, and the sorting of the grabbed target is completed. The traditional industrial robot visual sorting system uses classical computer vision theory, such as invariant distance, template matching, SURF feature and other algorithms to identify and locate workpieces, which has higher requirements on the scene environment, workpiece shape and background colour. The workpieces and objects on the on-site conveyor belt may have complex shapes and different postures and are densely placed together. In this case, the classical visual recognition and positioning algorithms cannot meet the requirements of high recognition rate and high precision.
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How an Edge-to-Cloud Data Platform Works - Litmus Automation Industrial IoT Case Study
How an Edge-to-Cloud Data Platform Works
At Litmus, the biggest challenge the customers face is access to the data they need to fuel machine learning and analytics models. Large scale manufacturers come to Litmus looking for the fastest way to connect to their assets and send data to the cloud. Companies not only need to send data to the cloud to create machine learning models, but they also need to deploy those models back at the edge with a unified edge-to-cloud platform. 
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AI in Flexible Processing Production Line of Automobile Powertrain - Shanghai SmartState Technology Industrial IoT Case Study
AI in Flexible Processing Production Line of Automobile Powertrain
At present, the field of automotive intelligent manufacturing is facing two major difficulties and pain points:First, the production line equipment is prone to failure and has a serious impact. Once the current production line equipment is shut down due to a fault, it will affect the production rhythm and reduce the output, or cause production stoppage in the worst case, causing huge losses to the manufacturer. Monitoring the performance status of production equipment and predicting faults is the key to ensuring the reliability of equipment to achieve normal production and operation.Second, it is difficult to realize automatic and flexible production changeover for traditional single-production lines. The traditional multi-variety manufacturing needs to build a separate line, the cost of production line construction is high, and the new product launch cycle is long, and it is increasingly difficult to adapt to the requirements of multi-variety, variable batch, equal emphasis on research and production, and mixed-line production mode.
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Manufacturing Optimization for Flexible Manufacturing Systems - AnyLogic Industrial IoT Case Study
Manufacturing Optimization for Flexible Manufacturing Systems
Flexible manufacturing system designModern machining shop floors require production systems that can be adapted to meet production problems as they occur. For technical reasons, most shop floor processes are automated, and, for economic reasons, the flow of materials and resources should also be automated to allow for long periods of unattended operation. The resulting systems are highly complex and would benefit from better forecasting and analytics.MCM has also found that when designing such complex systems for successful tender, precise dimensioning is necessary to win the bidding process. Further design challenges arise when trying to predict system behavior or plan reconfigurations. And, without knowing system behavior well, it is difficult to define machine control policies.A performance evaluation tool would help MCM address the challenges associated with FMS plant design. They wanted a tool to help support several activities:Performance evaluationInitial plant configuration supportAutomation dimensioning performance insightsInsights on component marginal utilityConfiguration comparisonsNew FMS plant management business opportunities 
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Commsignia Works with Audi and Qualcomm for C-V2X in Virginia - Commsignia Industrial IoT Case Study
Commsignia Works with Audi and Qualcomm for C-V2X in Virginia
Work zone detection is not cleard. Vehicle safety, road hazzards and fatalities are constraints.
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Vision-guided Robots Simplify Component Production and Inspection - COGNEX Industrial IoT Case Study
Vision-guided Robots Simplify Component Production and Inspection
Executing the pick and place processes for simultaneous delivery and quality control of raw materials and finished components on the production line.
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