What IIoT Means for the Food and Beverage Manufacturing Scoreboard
Today, the Industrial Internet of Things (IIoT) is no longer just a buzzword – the concepts are now widely understood, its value widely accepted and its adoption increasingly prevalent in the food and beverage industry. It's easy to see why the pick-up has been so swift. The food and beverage industry has seen specific useful applications of IIoT - in supply chain management, manufacturing operations management and predictive maintenance, to name a few. The Industrial Internet Consortium has described a 3-tier architecture (edge, platform, enterprise) that hosts the core IIoT platform capabilities of device management, data aggregation, data transformation, analytics and operations, along with the management of data flows between the tiers. While today IIoT is largely understood for data acquisition, many new aplications can be expected. The consortium runs a testbed program dedicated to ascertaining new innovations for their usefulness and viability.
Certainly, a network of connected equipment and systems that can communicate, analyse and respond to data can drive higher levels of efficiency is beneficial. So, what does IIoT really mean for manufacturers, when mapped back to the long-standing manufacturing metrics? Let’s address this from 3 key aspects:
1. Safeguard quality, safety and compliance
2. Maximise asset reliability
3. Continuous improvement
Leverage IIoT to safeguard quality, safety and compliance
Product quality is constantly top of mind for food and beverage manufacturers. Through effective quality control measures, manufacturers can reduce quality non-conformance incidents to minimum. Advanced analytics and the use of Statistical Process Control charts to detect specific trends allows for corrective and preventive actions to be taken swiftly and accurately. Connected equipment means that real-time production data, from many different sources, are obtainable and correlated to support analytics and provide objective evidence of compliance and safety. A full integration with the plant automation systems, including workflow and documentation management to provide accountability and traceability, makes it easy to enable quality control processes.
Analytics can maximise asset reliability
Unplanned equipment stoppage such as breakdown, especially in high frequency and long duration may cause a delay in production and thus delivery. Product quality issues caused by equipment and scrap due to equipment breakdown may also result in the failure to meet customer’s order quantity in time, and lead to increased manufacturing costs. Leading food and beverage manufacturers are quick to capitalise on big data and IIoT to mitigate these issues.
A manufacturing control system and manufacturing operations management system leveraging IIoT sensors and feedback can monitor equipment and process critical parameters to minimise breakdowns and quality incidents. This can be done both in real-time, and using predictive techniques to provide early warnings of failure. Predictive asset analytics reduces unplanned downtime and optimise output. A good asset analytics system is scalable and can be easily integrated with the manufacturing operations management system or with any other business system. In situations when breakdowns and quality issues occur, the connected system enables swift rectification actions. It also helps in data deployment and analysis to prevent the same breakdown and quality issue from reoccurring, thereby increasing equipment reliability to deliver the product on time and in full.
Continuous improvements empowered by IIoT
When presented with meaningful data, managers are empowered to make real-time informed decisions towards continuous improvements to increase productivity and reduce waste. A connected plant automatically collects, categorises, analyses and presents production data in ready-to-consume format. Some analytics can provide immediate feedback to operations teams for short interval control, allowing immediate and continuous improvement during the shift. The data however can help the engineer in identifying root causes of bottlenecks and breakdowns waste. This significantly shortens the time spent on manual data handling.
There are many other instances of how IIoT drives higher levels of collaboration and manufacturing efficiency. While approaches and results vary from company to company, operating assets are the heart of any operation. IIoT technology is a valuable new tool to help us better understand those assets and how they are operating, that can help support greater productivity and data-driven decisions.
Keith Chambers is responsible for strategic direction, commercialization and development for AVEVA's operations management portfolio globally. Keith has over 20 years’ experience in the automation, software and MES business with a focus on manufacturing operations software in the food and beverage, CPG and life sciences industries.