AI application

Diagram shows how Grantek Engineerin-a-Box connects cloud-hosted industrial development software to devices, when and where it’s needed, without sacrificing security. It received 2021 Engineers’ Choice recognition in the Cybersecurity category. Courtesy: Grantek

devices related to safety functions. Status and alerts go to designated personnel once a light curtain has been actuated. The device also can count number of safety light curtain device uses to help preventive maintenance. For safety devices that allow programming, it is crucial to identify which program is active, when it was programmed and who performed the programming. -David Schucker is marketing coordinator, Schmersal USA.

Adapt data, leverage skills, innovate

Industry 4.0 initiatives include three critical aspects for success when moving from data to databased decision making: data, people and analytics. 1. Adapt data for analytics: Foremost is the data and ongoing access to it, in legacy systems and industrial applications, because the best laid strategies will be tweaked and improved in the course of Industry 4.0 initiatives. The ability to start an advanced analytics project with the data where it is, in silos and different systems and of various types, is critical.

2. Leverage employee data skills for analytics:

Second, a consistent finding in successful Industry 4.0 projects is the recognition and leveraging of employees’ skills because these people best know the plants, processes, and procedures. 3. Integration: with access to the data and the right people, it’s time to bridge them and deliver innovation to those with the greatest abilities and needs. -Michael Risse is CMO and VP, Seeq Corp.

Artificial intelligence: mill optimization

Variability controlled with artificial intelligence (AI) software. A digital twin-based AI optimizer was deployed to run alongside advanced process controllers (APCs). Results include a 1% increase in mill production throughput with annual topline impact of $3-4 million for the mine.

The digital twin model was based on recurrent neural networks with self-adaptive tuning mechanism with these objectives: 1) AI-based approach with a supervisory level of decision-making support for APC. 2) Coordinated constraint management across the mill circuit to get the best out of mill controllers including APC. 3) Cognitive learningbased approach, factoring in operator and metallurgical engineer expertise and insights. 4) Continuous adaptation of AI-models to dynamically account for ore and process variations.

Typical advisories from the digital twin optimizer would include mill ore feed, power, load, water additions and mill speeds. The trained digital model deployed online with live data ingestion capabilities from plant distributed control system (DCS), lab computer systems and asset management systems, continuously predict, and run optimizers to provide adjustments of the APC control parameters in real-time. This allowed the APC to adapt with changing conditions and enable the grinding mill to perform at higher throughput levels. The AI software installation caused no disruptions to existing operations. -Dominic Gallello is chief executive officer (CEO) at Symphony AzimaAI.

Mission-critical should be the mission

For many applications, the cost of failure is too high not to have mission-critical capabilities in supervisory control and data acquisition systems. Control systems fail for three main reasons. 1) Architecture related failures in control systems are caused by single points of failure, limited levels of redundancy, and virtual redundancy with a single point of failure. 2) Cyber attacks include distributed denial of service (DDoS), ransomware and lack understanding that bad guys already may be in. 3) Underestimated cost of data recovery because of manual data syncing, data loss, and procedure complexity.

Five ways to build control system resiliency are system-wide redundancy, real-time system backup and bi-directional synchronization, integrated software platforms, application version control and fast response to vulnerabilities from the vendor. -Chris Little is media relations, Trihedral. ce

‘Results of using AI software

include a 1% increase in mill production throughput with annual topline impact of $3-4 million for the mine.’