SMART Edge and Energy

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SMART Edge and Energy

Overview

SMART Edge is a software program that is designed to let manufacturers apply smart manufacturing to their current manufacturing processes and equipment, in order to optimise the entire production process.

Currently, many of the traditional, legacy devices installed in factories around the world are unconnected as they have controllers and control languages that are not compatible with one another. This makes data collection and analysis a laborious task.

SMART Edge provides the common platform for monitoring the performance of these devices. It captures real-time data from manufacturing equipment and processes, and by analysing the data through fog and edge computing, it can help manufacturers make the right decisions to enhance the operational performance of their factories.

SMART Edge & Energy Monitoring System is an integrated computer edge system where the personalized digital footprint of each system is being acquired, tracked and monitored.

Application for SMART Edge:

Equipment Health Monitoring and Reporting
Preventive and Prescriptive Maintenance
Process Signature Verification and Analytics

Application for SMART Energy:

New Equipment with built-in Energy consumption meters
Legacy Systems that do not have a digital footprint
Ad-Hoc Energy consumption Monitoring

System Scalability

Line To Factory Traceability

Features

Machine learning to establish “personalized” device characteristics (such as current, voltage, temperature, vibration)

In manufacturing, devices commonly perform a specific task repeatedly. During this task, sensors can be used to measure physical attributes (force, distance etc.). The signals from the sensors are then digitized, and a “personalised” signature (waveform) that is specific to a particular device is formed. Machine learning is then applied to this signature to acquire the performance characteristics of the device.

Customised learning features based on parameters to be monitored

Based on the personalised characteristics of the device, the normal operating parameters will be formed.

Real time monitoring of device health status and reporting

Should any of the physical attributes of the machine exceed or fall below the normal operating parameters, the user can then be warned via multiple messaging options (e.g. e-mail, WhatsApp) to take corrective action. Thus, the device health is monitored in this manner.

Predictive and prescriptive reporting based on “learned and personalised” data

Based on all the data obtained, user can perform predictive or even prescriptive maintenance.

Process Monitoring

In the same way, this data collection and analysis process can be applied to production processes, and the process “signature” will be formed. Based on the data, users will be able to tell if there are any abnormalities in the process and corrective action can then be performed in a timely manner to ensure that product quality is under control.