Most manufacturers see investments in factory connectivity not just as a means of cutting costs, but also as a way to increase revenue. In fact, respondents to the Annual Manufacturing Report 2017 anticipate additional revenues of £775,000 (€873,000) in the next 12 months because of their investments in connectivity. Automated engineering is not about engineering humans out of the production process. Regardless of how a control system is used, whether it is by manual code writing or by setting parameters for production — it is always humans who complete this task. However, one of the most talked about advantages of automated engineering is the reduction of complexity and repetitive tasks for human workers. Rather than setting parameters before every batch of production or inputting end of shift reporting across multiple machines, automated engineering can remove these menial and time-consuming tasks. Using automated engineering, a project engineer can design individual automation applications in a faster, easier and more accurate way. Furthermore, automated engineering allows data to be easily linked with other systems like planning software – set production to run automatically and eliminating the need for manual programming with error-free results. Machine builders, for example, can reduce their time-to-market expectations using automated engineering. Reusable base projects mean that the design work required to bring a new machine to market is already prepared. The time spent on mundane programming tasks is reduced, fewer resources are required and, as a result, profits are increased.

Increase flexibility, meet production deadlines

Some 44 per cent of respondents to the Annual Manufacturing Report 2017 stated that they expected production flexibility to improve because of investments in connectivity. By applying automated engineering to the factory floor, manufacturers can shift from a traditional manufacturing model to a much more flexible and efficient production line. Consider a pharmaceutical manufacturing facility as an example. If one of the ingredients needed for the manufacture of a certain medicine has not arrived at the facility, the plan for that shift could be severely disrupted. Usually, it would be the responsibility of the production manager to decide how to rectify this problem. However, intelligent software can assist in making this decision based on data, rather than guesswork. Inventory and customer demand data can be collected and analysed automatically, to identify what medicine could, and should, be produced in its place. In addition, rather than delaying production due to the lengthy process of manually reprogramming the production line, automated engineering can use set parameters to begin production as soon as possible.

Minimise consumption, enhance efficiency

Waste reduction is one of the most effective ways to increase the profitability of a business, and manufacturers have long hailed the advantages of using lean production methods to decrease or eliminate waste. Automated engineering provides manufacturers with a greater visibility of facility-wide data, allowing them to quickly identify exactly where waste could be reduced. Excessive inventory, as an example, can often result in money sitting on the shelf of a factory or simply gathering dust in the warehouse. Automated engineering can ensure that requirements for different types of production are visible by all, including the planning department. For example, before orders of raw materials are placed, visualisation of customer demand data and production plans can ensure that the correct amount of each material is ordered – reducing waste and increasing efficiency. The same process can be scaled to reduce energy waste from building operations. One of the advantages of COPA-DATA’s industrial automation software, zenon, is its scalability. The software is primarily used to monitor production data, but it can also monitor and control building or energy management data. For instance, zenon can highlight peaks in energy consumption during the production process. Using this data, production managers can easily identify why these peaks have occurred and make the necessary adaptions to reduce waste. This process can reduce resource and energy waste and ensure machines are used more efficiently. Before an organisation has collected and thoroughly analysed its production data, it is difficult to identify the areas of production that could change to save money or enhance profits. Manually analysing data from the factory floor is not only difficult, but it is almost impossible. Over two-thirds of manufacturers have made investments in automation in the past 12 months and implementing intelligent automation software should be the first step to understanding the data this automation generates. Author: Lee Sullivan, regional manager of industrial automation software specialist COPA-DATA UK www.copadata.com