In today’s discrete manufacturing, a high degree of automation, increasing robotisation, industry 4.0 and smart factory principles help to improve efficiency and maintain competitiveness. For machines within manufacturing, the key indicator is overall equipment effectiveness (OEE), which is a measurement of manufacturing productivity based on availability, performance and quality. Any failure or underutilisation of machinery and equipment can have a negative impact on the production output. Many plants have room for improvement in terms of efficiency. On average, they achieve only 65% efficiency, which means capacity is not fully utilised. There is an obvious opportunity to increase productivity. To ensure the reliability, availability and process stability of manufacturing equipment and systems, cross-divisional transparency is crucial. Without real-time insight into machinery health and process performance, production can be delayed, quality can suffer and unplanned downtime may occur.
Improving sustainability in production
A key step to the success of sustainability strategies is monitoring usage – understanding the behaviour and what is normal for a given process. Manufacturers may not be aware of how much energy, water, raw and primary materials their processes consume throughout the value chain. This lack of awareness leads to inefficiencies and wasted resources. Because of this, identifying and assessing resource consumption and production emissions on-site is crucial. It is essential for manufacturers to gain awareness of energy consumption to make potential cost savings tangible. With an appropriately digitised production environment is it possible to continuously measure and optimise sustainability efforts. To support sustainability goals, experts must first identify and prioritise areas of energy consumption and then implement the right technologies, such as sensors that extract the right data and software tools that evaluate extensive data streams to deliver key insights. This kind of real-time information can be used to track energy consumption and identify and correct issues at an early stage. Informed decision-making can reliably minimise environmental impact, improve energy efficiency and guarantee compliance with regulatory requirements.
Caption: A floor to cloud approach enables manufacturers to identify optimisation opportunities and continuously improve operations.
New automation architectures
The manufacturing industry is currently undergoing a major shift in terms of adopting automation technology, moving from simply deploying individual smart components to implementing entire digital ecosystems. That doesn’t mean existing automation technology is being replaced – instead, components and the various vertical layers of a production landscape are linked within a digital ecosystem. This is because smart devices add greater value when they can interact with other automation components. Equally, software cannot support improvements without leveraging additional data. by integrating hardware and software into a digital ecosystem can manufacturers obtain added value.
The automation architecture currently used by manufacturers will need to transition to ensure data from sensors and hardware within the operational technology (OT) layers is integrated appropriately with the information technology (IT) layers. In addition, the people who operate in each layer will need to expand their skill sets or leverage new digital tools that enable greater connectivity. Today, unoptimized connectivity of the OT and IT layers presents a barrier to meaningful data use because there are separate layers of automation and network architectures. Modern automation architectures enable manufacturers to manage, connect and deliver operational technology (OT) and information technology (IT) data seamlessly across their plants. Data is gathered from devices and modern edge-based technology control systems and securely moved to today’s cloud-based enterprise for analysis, trending and forecasting. This supports efforts to optimise the process, reliability, safety and sustainability.
However, because every manufacturing company is different, this requires not only a common set of principles and specifications, but also flexible automation architecture that can be configured to the specification of each manufacturer. Architecture flexibility is important, not only in terms of providing the opportunity to start small and scale up, but also supporting adjustment of production lines to meet changing market demands.
Smart devices and sensors, controllers and edge computing hardware and analytics software enable existing machines and processes to be optimised, and workforces to achieve ambitious productivity and safety goals, and companies to meet their sustainability targets. Using a methodology such as Emerson’s Floor to Cloud™ approach, manufacturing data is acquired, translated and presented by modern human machine interfaces to provide insights into a plant’s condition and performance. The aim of a floor to cloud approach is to acquire real-time data to enable manufacturers to identify optimisation opportunities and continuously improve operations. By implementing advanced sensor technology, analysis software and networking solutions, manufacturers and original equipment manufacturers (OEMs) can access and analyse machine data. Critically, real-time diagnostics are possible, which provides the opportunity to improve OEE, sustainability and production safety.
Caption: Controllers and edge computing hardware collect data from smart devices and sensors, with analytics software presenting actionable insights to enable existing machines and processes to be optimised.
Access to data
A key element of a floor to cloud approach is to reduce the technology barrier of entry, while enabling the access to data for the right range of users. By extending the availability of real-time operating data from an individual device or system, not only manufacturers, but also OEMs and automation vendors can identify issues and make informed decisions that positively impact the management of a plant. For example, real-time trends and diagnostics can be used to perform predictive maintenance processes that improve equipment availability or analyse root causes to achieve better product quality and continuously optimise systems and operational production processes. Utilising external expertise from the machine builder or automation vendor can supplement a manufacturer’s in-house maintenance team. It is also very important to get access to this data without having to redesign an entire machine. Equally, users want to perform analysis and optimise machines without having to access the data from a control system. The use of smart gateways and edge controllers that support both deterministic control and analytical software helps to achieve this.
A typical floor to cloud approach incorporates intelligent devices and individual components connected to controllers, edge devices or gateways. Automation vendors don’t offer solutions for every production environment, but standard communication protocols allow components from different companies to connect and operate within the digital ecosystem. The technology must be as easy as possible to implement. These devices have plug-and-play capability, with appropriate interfaces for communication via OPC UA or IO-Link. Software solutions such as Emerson’s PACEdge or Movicon offer similar connectivity and can present analysed data to support predictive maintenance strategies, optimisation of OEE, or reduced energy consumption.
