A Remote Monitoring and Analytics Platform for Manufacturing Engineers

Conventional factory management and process control systems are integrated on site, requiring monitoring, management and intervention from engineers directly on the factory floor. However, with the recent lockdown imposed by the COVID-19 outbreak, many manufacturers have been forced to either reduce production throughput due to implementation of social distancing initiatives, or else suspend production indefinitely.

Such manufacturing companies may have been designated as a 'nonessential business', however often the products they manufacture, for example, hard-disk-drives, machine parts and medical components, are essential to facilitate working from home, derive innovation and maintain societal harmony. For manufacturing companies, the financial impact of this can lead to business closure and the redundancy of employees.

Since manufacturing companies often recruit employees in a range of roles from the surrounding geographical area, this can lead to the decline and deterioration of communities which are already struggling due to the restrictions imposed by the lockdown.

With advanced data analytics becoming a key enabling technology across the manufacturing sector, there is now the potential for automated large-scale process systems to make the most of the large volumes of data they collect, and furthermore for users to remotely manage the analytics underpinning the manufacturing process. Advanced Analytics Labs (AAL) are developing a cloudbased Remote Monitoring and Analytics Platform for the manufacturing sector.

The platform will enable production engineers and managers to remotely view factory state, interact with AAL's advanced machine learning models and communicate with on-site staff to effect changes in the production process. This would represent a step-change for how the factory floor can be managed in a remote fashion, for both this and potential future pandemics, or even if remote working is sought to become the norm.

Using the tool, engineers and process managers will be able to view the status of their production schedule and current units passing along the manufacturing process, remotely. Additionally, the advanced analytics models which provide predictions on final product quality using novel multivariate analytics can be used to make suggested/theoretical changes to a digital twin, in order to determine the optimal way of making reworks to bring units back to specification, an enabler for facilitating a circular economy for companies.

The messaging/workspace component of the application may be used to share the optimal rework strategy for specific units with the skeleton factory floor staff on site, thereby further facilitating transition to Industry 4.0 in the era of advanced analytics.