IoT Use Cases Representing Real Business Impacts for Manufacturing

Internet of Things (IoT) is one of the major drivers for third industrial revolution. Connectivity of things affects and will continue affecting business in future. It’s still early days for the IoT but everyday a little part of its burgeoning ecosystem becomes a factor in our lives, whether we know it or not. From industrial tools to farming to cities to grocery aisles and everything in between, the IoT is there.

We'll be discussing about four noteworthy Manufacturing IoT use cases that demonstrate positive Return-on-Investment (ROI). Here it all, goes for you.

  1. Monitoring Assets in Operation:
  2. In looking at your maintenance strategy for your machines and equipment, IoT can be applied so you can monitor your assets while they’re in operation. For example, a bottling plant may fill thousands of bottles per minute and has hundreds of small motors. These motors typically aren’t monitored individually and follow a break-fix/replace approach. A large bottling facility recently that adopted IoT technologies monitored these motors and discovered that micro stoppages from these motors accounted for one of the top downtime sources in the plant. By applying improved maintenance approaches to these motors, unplanned downtime was reduced by over 10 percent. Additionally, keeping assets up and running has the potential to significantly decrease operational expenditures, saving companies millions of dollars. With the use of sensors, cameras and data analytics, managers in a range of industries are able to determine when a piece of equipment will fail before it does. These IoT-enabled systems can sense warning signs, use data to create maintenance timelines and preemptively service equipment before problems occur.

    By leveraging streaming data from sensors and devices to quickly assess current conditions, recognize warning signs, deliver alerts and automatically trigger appropriate maintenance  processes, IoT turns maintenance into a dynamic, rapid and automated task.

    This approach promises cost savings over routine or time-based preventive maintenance, because tasks are performed only when they are needed. The key is to get the right information at the right time. This will allow managers to know which equipment needs maintenance; maintenance work can be better planned; and systems remain online while workers stay on task. Other potential advantages include increased equipment lifetime,  increased plant safety and fewer accidents with negative environmental impact.

  3. Managing Recipe Variation:
  4. Brewing beer is a complex process that includes almost infinite variations in recipes. One of the largest craft brewers in the U.S. recently engaged in an IIoT project using machine learning and historical process data to solve a batching problem that was resulting in a major quality issue and the loss of entire batches. The brewmasters thought the problem was the relationship between pressure and temperature; it turned out to be an issue with the timing of batch processes determined by natural variances in yeast.

    Using collected data, the brewmasters built a model to alter the recipe and optimized batches on previously unknown relationships. With the new process established, they eliminated lost batches for this quality issue and recaptured two weeks of extra capacity per lost batch.

  5. Reduction in the Quality Testing Cost:
  6. Quality testing and validation comes at a price and is often a significant contributor to the total cost of quality incurred by a company. Because of these costs, quality best practices dictate that instead of testing every finished product, industrial companies should monitor the production process itself. By ensuring the process is error-proof, the outcome is consistent quality levels. IoT and smart connected products are changing this game.

    One smart connected products company is using new connectivity and intelligence capabilities in the end product to conduct quality testing during production and feedback is being used for additional quality improvements.

  7. Smart metering:
  8. A smart meter is an internet-capable device that measures energy, water or natural gas consumption of a building or home.

    Traditional meters only measure total consumption, whereas smart meters record when and how much of a resource is consumed. Power companies are deploying smart meters to monitor consumer usage and adjust prices according to the time of day and season. Smart metering benefits utilities by improving customer satisfaction with faster interaction, giving consumers more control of their energy usage to save money and reduce carbon emissions. Smart meters also give power consumption visibility all the way to the meter, so utilities can optimize energy distribution and take action to shift demand loads.

    Major Utilities include...

    • Reduction in operating expenses by managing manual operations remotely.
    • Improvement in forecasting and streamline power-consumption.
    • Improvement in customer service through profiling and segmentation.
    • Reduction of energy theft.

Simplifying micro-generation monitoring and track renewable power  Hence, Industrial Internet of Things combined with Machine Learning helps companies dig into all the data from every machine, facility that the sensors and controllers are accumulating in order to reveal actionable solutions that could transform the Business. It is done by quickly and cost-effectively pin- pointing the gaps in production, maintenance, supply chain and even in customer retention to reveal opportunities for immediate improvements.

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