In order to further improve the sustainability balance, manufacturing companies should also bring together the topics of Industry 4.0 and ESG (Environmental Social Governance) goals. V. R. Vijay Anand, Head of Digital Machining at Sandvik Coromant, explains how data can contribute to this and why it is the key to reducing the waste problem in manufacturing.

Despite the use of digital tools, only 59% of manufacturing companies cite an improved sustainability balance as a reason for digitalizing their processes. Data collected by the Swedish Engineering Industry Association underlines the enormous importance of digital tools for achieving sustainability goals. For example, the use of IT technology in areas such as manufacturing has the potential to reduce overall CO2 emissions by up to 20 percent.

The increased use of digital tools and processes is therefore crucial in order to bring manufacturing in line with the Paris Agreement as well as to increase resource efficiency and reduce the amount of waste. Current data from the World Bank shows that the need is great: according to this data, the amount of waste generated in industry worldwide is almost 18 times higher than that in municipalities. And a large proportion of the waste generated in production facilities is considered avoidable.

Overproduction and production errors are two of the most common reasons for the high volume of waste. Too many industrial plants are still working with outdated technologies that are not up to the challenges of modern production. Nevertheless, the enormous amounts of waste are not an unavoidable consequence of production. Data can play a key role in reducing industrial waste - if manufacturing companies know what to do with it.

Improve operational efficiency

Every production plant, regardless of its size, complexity or age, generates a considerable amount of data every day. In a smart factory, it is collected using sensors installed on every machine. Utilizing such machine data, from equipment performance to product quality, is the first means of reducing waste on a large scale.

Even small changes to individual processes add up and can have a major impact on operational efficiency. Collecting and analyzing machine data in production makes it possible to monitor and control the machines. By identifying inefficient processes, optimizing production and logistics planning and predicting upcoming maintenance needs, each individual process can be improved, and by making many smaller processes more energy efficient, overall energy consumption can be controlled and reduced.

Real-time energy inefficiency detection enables manufacturing companies to identify potential causes and solutions for energy waste: for example, a machine that consumes significantly more energy than others. Using this information, the cause of the increased energy consumption can be identified and improvements introduced to optimize machine efficiency and thus reduce energy waste.

Defective, faulty machines can produce a lot of waste. Continuous real-time data analysis helps to optimize machine maintenance and rectify faults quickly: by detecting problems before they occur. Machine performance data can help to immediately detect the smallest changes in machine behavior. Based on this, engineers can in turn carry out predictive maintenance - and ensure that faulty products are not produced in the first place.

The CoroPlus range in the field of Data Driven Machining helps manufacturing companies to improve their efficiency, reduce waste and increase productivity. CoroPlus Process Control monitors machines in real time and triggers the necessary measures according to programmed protocols. If certain predefined problems occur, a corrective action is automatically initiated - for example, stopping the machine or changing a worn cutting tool. This type of maintenance improves operational efficiency by up to 89% and reduces waste by using data analysis to monitor machine performance and detect potential faults before they occur.

Considering the entire life cycle

Life cycle assessments (LCAs) also generate data that contributes to waste reduction. A life cycle assessment evaluates the environmental impact of a product holistically in every phase of its life cycle. It takes into account the environmental impact of raw material extraction, the resources required, material and energy consumption during production, packaging and distribution, as well as the effects of the functional use of the product, waste volumes and environmental pollution at the end of its life.

By looking at each individual phase of a product's life cycle, a life cycle assessment clearly reveals a product's sustainability shortcomings. What's more, it also shows how sustainable products that are still in development will be and supports the creation of more sustainable alternatives.

It is not only the products themselves that need to be considered, but also their packaging. Packaging causes many environmental problems due to its high resource requirements. This can be observed worldwide. In the UK, for example, trade and industry generate almost 44 million tons of packaging waste every year. In the USA, 28 percent of all municipal solid waste is attributable to packaging.

Sandvik Coromant has recognized the problem of packaging waste and introduced a Package Selector Application (PSA). The PSA uses data to analyze a 3D CAD model of the product to be packaged, identifies its key points and uses an AI algorithm to recommend the smallest possible amount of packaging. This reduces packaging waste and improves the eco-balance of Sandvik Coromant tools.

Circular economy through transparency

Data can also be used to promote a circular economy in production. This involves establishing a closed production chain in which waste from one process is used as a resource in another. Continuous reuse minimizes the amount of waste as much as possible.

Using life cycle assessment and machine data, manufacturing companies can optimize the efficiency and recyclability of their products through continuous product and process adjustments. The efficient implementation of such a production system requires a reliable data strategy. For a solid data architecture, manufacturing companies need a digital infrastructure that can easily synchronize operations - potentially across multiple sites - and identify opportunities to leverage waste. Sandvik Coromant's CoroPlus offering of machine connectivity and sensor-integrated tooling solutions makes digital machining accessible to manufacturing companies, equipping them with exactly the cutting data they need to utilize their waste resources for a more sustainable operation.

Given the sheer volume of data generated by industrial companies, it can be difficult to decide which data to use. But with the right usage strategy, it becomes an extremely valuable tool for reducing industrial waste - by improving efficiency, enabling predictive maintenance, stimulating the development of innovative products and optimizing the resource management of machines, plants and even entire companies.