April 2020

31 www.drivesncontrols.com April 2020 understanding what will be possible in the short, medium and long terms, and how easy or difficult it will be to match the goals of the organisation in becoming a smart operation. The good news is that whatever level an organisation is currently at, with good project planning and communications, the journey towards digitalisation and smart manufacturing can be achieved to the appropriate level for the organisation. Adopting standards for machine control and network connectivity simplifies the process. In the food & beverage and packaging industries, for example, organisations are frequently operating in multi-vendor automation environments and using the OMAC PackML and OPC UA standards to achieve better integration. Not natural bedfellows In the past, the worlds of IT and OT have not been natural bedfellows, with the OT world operating in real time with process speeds measured in milliseconds or below, and the IT world operating at much more extended sampling times of minutes, hours or even longer. There has been a natural divide between these two worlds, but the advent of edge computing technologies that sit in the space between the two has made the integration of these seemingly diverse worlds much easier, and allowed a greater level of choice about where data analysis takes place. It is easy to assume that if the necessary levels of automation and network infrastructure either already exist on plant, or as the first phase of an implementation plan to become smart, the natural extension of this is to just collect every byte of data available and sit back and admire what has been achieved. Of course, it needs to be more scientific than that. Inevitably, enhanced communications in recording those machine “conversations”will create the need to manage much larger volumes of data. This requires the creation of a platform for efficient data analytics and data transfer between the OT and IT levels. The challenge is to handle all of that data in a structured way, filtering out unnecessary“noise”and turning the“data”into “information”. Not losing sight of our goal of becoming a smart manufacturing plant, analysing this data will offer the ability to visualise all of the important aspects of production: OEE (overall equipment effectiveness); productivity; quality control; use of raw materials; waste; and predictive and preventative maintenance – all of which are familiar to production directors tasked with making operations more efficient. The question is often:“Where should we implement our data analytics?”Is it best to move everything to enterprise-level servers, or even the cloud, or is there an alternative? Of course, the new smart technologies appearing at the edge not only offer an alternative, but improve flexibility and the efficiency of data management. Edge computing technologies offer industrialised systems that are designed to live in the plant environment like other automation equipment, and to be at the“sharp end”of the data-collection process. As discussed previously, the worlds of IT and OT are often divided by the frequency at which data is sampled, but edge systems offer the chance to perform sophisticated data analyses incorporating AI (artificial intelligence) algorithms in real time, and therefore interface with the plant automation systems at high speed, making machine learning and improved production efficiencies a reality. The next major benefit to carrying out data analytics at the edge layer is that the data can be filtered, with only the necessary and relevant data being passed on to the enterprise or cloud-based servers. This can reduce the cost of data processing at this level considerably, because cost is often related to the number of data points being processed. It is clear that by linking the worlds of IT and OT, the edge classification of technology is playing a key role. Into this space, Mitsubishi Electric has recently launched its MELIPC edge computing system which takes care of all connectivity issues“downstream”to the plant level, and supports all of the main open networks. It removes the problem of interfacing to machines or plant assets controlled by different automation vendors, and provides a real-time data-logging and processing environment in a rugged form factor. The system has a dual operating system – Windows and VxWorks RTOS – giving the flexibility to embed third-party applications into either environment. Its internal structure follows a framework defined by the Edgecross Consortium – an independent organisation with more than 200 members, whose goal is to standardise the interface between the OT and IT layers. Ensuring consistency One of the biggest challenges faced by manufacturing industry is to ensure that final product quality remains consistent, independently of variable environmental conditions, raw products and in-feed ingredients. Many organisations have“optimised”their plants, but what digitalisation and smart manufacturing offer in addition to this, is the ability to move to a predictive model based on a strategy of continuous improvement. If this is followed to its ultimate conclusion, the whole plant ecosystem, including energy and the supply of raw materials, can be integrated and made operationally efficient. The seamless vertical connections between OT and IT also open up manufacturing industry to new business models such as “batch size one”, or rapid changeovers of one product line to another to keep pace with fast-moving consumer trends. One of the key takeaways from this march of change in systems, technology and networking, is that it can be applied equally to existing production lines and equipment and to new factories. Manufacturing by its nature is now a mature industry, so upgrades and progress inevitably involve managing change, not just for physical plant and software layers, but for people too. All manufacturing plants have the capability to become smart operations. The journey to that goal may be short or long, but with the right planning, investment, and partnering with the right automation vendors, it can be achieved step-by-step. n DIGITALISATION n