How Remote Monitoring and IIoT Improves Machine Maintenance

In 2020, remote operations and management evolved as an important aspect across industry 4.0. Thanks to the developments in IoT sensor technologies and wireless connectivity, industries can make a coherent transition to remote monitoring that assures business continuity and maximal performance 24/7.

With the help of real-time and historical data of processes, assets, industries can better handle production, maintenance and increase safety across several sites. IIoT is modifying the way manufacturers recognize concerns on the plant floor. Except the plant floor, conventional alerts don’t give much information about the root of disruptions or maintenance trends. But manufacturers can now utilize the IIoT to enlarge the abilities of managing maintenance monitoring systems.

IIoT removes data silos, so device-level data is available to the whole operations team. It offers valuable real time insights into machine performance, process inefficiencies etc. Manufacturers can utilize the data to improve Overall Equipment Effectiveness (OEE), which is an estimation of manufacturing process efficiency.

IIoT and Machine Monitoring

In a today’s world of constant connectivity via smartphones, social media and the internet, manufacturers are taking benefits of the latest technology that connects us all together. Remote machine monitoring and the IIoT is supporting to simplified efficiency while keeping high levels of security as well as integrity. As per MPI report, 76% of manufacturers predict that remote machine monitoring technology will consider for increasing customer satisfaction.

In the past, wireless systems were hard to install and maintain. Today remote monitoring solutions can be combined into a single, low-cost unit. Some of the key features of this integrated system involve:

• Flexibility: I/O devices that manufacturers can simply install /uninstall and switch to a new location as monitoring requirements changes.
• Fewer Maintenance: The I/O terminals and LCD screen are involved within a single housing. This means lesser mechanical and wiring concerns requires to be included into a maintenance schedule.
• Improved Data Analysis: A single wireless I/O device can assemble both digital and analog sensor readings and send this data to a central collection point for analysis. And then there are multiple sensor readings that can be merged into a single gateway device before moved to a host-controlled system for monitoring.

Operators and Plant managers are now easily access device level data, offering valuable insights into OEE, analyze and improve the performance of equipment under their control. OEE is estimated by combining three different production metrics such as availability, performance and quality.

The outcomes of this calculation give actionable insights into the crucial sources of waste in a manufacturing operation. And this is where access to data from sensors as well as indicator lights become very essential. Logged data from sensors and indicator lights located on machines can assist manufacturers to calculate OEE and recognize procedures to enhance efficiency of their machines and processes.

Condition Monitoring and Predictive Maintenance

Condition-based Monitoring and Predictive Maintenance are two maintenance schemes which focus at optimizing equipment efficiency and minimizing service timing and costs during equipment life cycle. Predictive Maintenance is basically relies on Condition Monitoring where flaws detection and classification algorithms, combines predictive models which can evaluate the remaining machine runtime left, as per detected flaws.

This perspective utilizes a broad range of tools, likewise statistical analyses and Machine Learning to estimate the state of the equipment. Wireless sensor networks also offer continuing insight into overall machine health. Real-time data helps indicate flaws that may tends to future breakdowns. In the past, interpreting minor performance modifications was not easy because technicians required to execute device-level tests to interpret machine health.

Manufacturers can easily track machine vibration, which is a key root of machine maintenance concerns. Machine vibration is frequently related to imbalanced, disordered, loose, or drawn parts. 

By remotely monitoring several machine components, shop floors can recognize excessive vibration before it causes unplanned downtime. With condition monitoring solution, a machine learning algorithm starts a vibration standard for the machine. When a machine is going beyond its threshold limit, the wireless temperature and vibration sensors can provide data in terms of alerts on users mobile phone through email or text message. The IIoT enabled sensors also can transfer vibration and temperature data to a wireless logic controller or PLC for collection and monitoring purpose.

Analyzing and Tracking Performance

Previously, machine operators need to manually analyze machine slowdowns or disruptions, which frequently needs additional man-hour and inefficiencies. The cost to find a root cause, in terms of downtime, was high. The threat of unplanned downtime was also high, as there was no other way to recognize the requirement for maintenance or repairs, other than the utilization of historical patterns.

IIoT-enabled alerts offer both the local machine status as well as remote status of each light module. Remote status indicators and other alert systems enable users to set down trends in machine uptime and cycle counts. Leveraging this data assists plants to discover maintenance intervals and make decisions regarding new machine investments.

It also supports manufacturers to  recognize whether a machine or operator is causing a congestion. Plant managers can utilize real-time data collection to precisely confirm when the delays were the result of machine downtime or operator inefficiency. For larger manufacturers with several plants, these trends can be transferred to a central location and compared with plant to plant to recognize and recreate the successes of the highest-performing plants.

Remote monitoring abilities will continue to recognize and rectify waste within their facilities. Developments in integration abilities will continue to reduce costs and lead times during IIoT implementations. With this manufacturers can easily collect data needed to recognize the root cause of production concerns and implement measures to improve efficiencies and prevent future interference. With the future of industrial operations undetermined, industries must stay flexible and adaptable. 

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