1 IoT Fundamentals: Definitions, Architectures, Challenges, and Promises
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manufacturing has worked to increase the amount of automation in the process.
Some benefits were realized, but often new technicians were needed to ensure the
automation was working optimally. The Internet of Things should improve this
situation as automation can be better monitored and controlled. A networked control
system can sense, visualize and control every aspect of the manufacturing process
even remotely. The smart factory can deliver a cost-effective, efficient, sustainable,
and safe manufacturing system.
Real-Time Quality Control Manufacturing business success is dependent upon
a rigorous inspection process applied across each production phase. IoT enables
manufacturers to program equipment and utilize big data analytic frameworks
within factories to effectively monitor the manufacturing line, equipment, raw
materials quality, and the quality of completed products at each point in the
manufacturing process. Integrating IoT in this manner provides the following
benefits to the quality control process:
• Enabling real-time action in alignment with the manufacturing process
• Optimizing in-process manufacturing using production engineering insights
• Continuous adaptation and learning based on production output
• Continuous optimization to address process drift or production variance
Predictive Maintenance The ability to predict difficulties or perform predictive
maintenance is an advantage with increased uptime and safety. Predictive maintenance is repairing or replacing equipment or components before predicted failures.
Traditionally, historical mean time between failure data was used to schedule this
maintenance, but with more accurate and timely data from IoT devices, a more
specific time can be found, meaning good parts are not replaced, or unexpected
weaknesses can be located and addressed before catastrophic failure. Of course, the
data must be analyzed to extract these benefits, using machine learning and other
data analytics techniques as mentioned earlier.
Safety Employee safety is another area that can be improved with IoT devices.
Workers can be observed to find lapses in focus or other mistakes, and preventative
action can be taken. With increased knowledge of activities on the floor, should
there be a problem, help can be dispatched more quickly and accurately. When all
activities are analyzed, it is possible to discover new processes or methods to use
during the manufacturing itself. There is the potential to improve efficiency with
these process ideas or with real-time solutions as situations develop in the plant.
Supply Chain Management IoT can help with supply chain management, as
sensors track and help manage the location and condition of inventory, management
can better plan, and schedules can be adjusted to optimize output. In addition
to sensors, IoT devices can be used directly for automation. Integrating robotics
can improve worker safety and factory throughput and reduce costs by increasing
efficiency.
Machine as a Service (MaaS) This approach will allow updated machines to be
deployed from the cloud, with remote configuration, connectivity, and monitoring.
31
manufacturing has worked to increase the amount of automation in the process.
Some benefits were realized, but often new technicians were needed to ensure the
automation was working optimally. The Internet of Things should improve this
situation as automation can be better monitored and controlled. A networked control
system can sense, visualize and control every aspect of the manufacturing process
even remotely. The smart factory can deliver a cost-effective, efficient, sustainable,
and safe manufacturing system.
Real-Time Quality Control Manufacturing business success is dependent upon
a rigorous inspection process applied across each production phase. IoT enables
manufacturers to program equipment and utilize big data analytic frameworks
within factories to effectively monitor the manufacturing line, equipment, raw
materials quality, and the quality of completed products at each point in the
manufacturing process. Integrating IoT in this manner provides the following
benefits to the quality control process:
• Enabling real-time action in alignment with the manufacturing process
• Optimizing in-process manufacturing using production engineering insights
• Continuous adaptation and learning based on production output
• Continuous optimization to address process drift or production variance
Predictive Maintenance The ability to predict difficulties or perform predictive
maintenance is an advantage with increased uptime and safety. Predictive maintenance is repairing or replacing equipment or components before predicted failures.
Traditionally, historical mean time between failure data was used to schedule this
maintenance, but with more accurate and timely data from IoT devices, a more
specific time can be found, meaning good parts are not replaced, or unexpected
weaknesses can be located and addressed before catastrophic failure. Of course, the
data must be analyzed to extract these benefits, using machine learning and other
data analytics techniques as mentioned earlier.
Safety Employee safety is another area that can be improved with IoT devices.
Workers can be observed to find lapses in focus or other mistakes, and preventative
action can be taken. With increased knowledge of activities on the floor, should
there be a problem, help can be dispatched more quickly and accurately. When all
activities are analyzed, it is possible to discover new processes or methods to use
during the manufacturing itself. There is the potential to improve efficiency with
these process ideas or with real-time solutions as situations develop in the plant.
Supply Chain Management IoT can help with supply chain management, as
sensors track and help manage the location and condition of inventory, management
can better plan, and schedules can be adjusted to optimize output. In addition
to sensors, IoT devices can be used directly for automation. Integrating robotics
can improve worker safety and factory throughput and reduce costs by increasing
efficiency.
Machine as a Service (MaaS) This approach will allow updated machines to be
deployed from the cloud, with remote configuration, connectivity, and monitoring.