The significance of materials technology and non-destructive testing is bound to grow in the future, as digitalisation and sustainable development start to place new requirements on products and components. Materials technology parameters are chosen based on standards, which means that the real potential of using materials technology to optimise the properties of materials according to their intended use is lost.
The current craze is innovation ecosystems, which offer one way to bring experts in different technological disciplines together with businesses to brainstorm new approaches. The role of materials technology and non-destructive testing in production chains is the subject of a project called “Smart Manufacturing in an Ecosystem”, which is a research collaboration between Tampere University and local mechanical engineering businesses and funded by Business Finland. 

The project promotes the development and reinforcement of a multidisciplinary mechanical engineering business ecosystem while also producing data that can potentially be used more widely going forward. The businesses involved in the project include Sandvik and several other businesses. The ecosystem engages in multidisciplinary cooperation with various units of
Tampere University (Engineering Materials Science, Automation Technology and Mechanical Engineering) and internationally with RWTH Aachen University. The ecosystem believes in the power of working together: none of the organisations can control everything alone, but by pooling their resources they can make significant contributions.
Better quality control required to improve machining techniques
Non-destructive testing (NDT) refers to a range of analysis techniques used to evaluate the properties of components without damaging them so that they can be used normally for their intended purpose after the testing. Industry uses NDT, for example, to check the standard of work in finished components. 
NDT generates real value when it is used to ensure that finished components comply with the relevant requirements. Raw materials can be analysed to ensure their quality, but final inspections are usually not performed until the end of the production process when the component is finished and can only be “accepted” or “rejected”. 
In the context of different machining techniques, NDT can be used to check that grinding, for example, has not resulted in grinding burns, which can shorten the fatigue life of components. Damage caused by machining during the production process can rarely be spotted by visual inspection alone. With respect to grinding, the key parameter is the temperature between the grinding wheel and the component, which must not get so high as to cause microstructural changes or residual stresses. 
Only NDT can detect this kind of damage. The useful properties achieved by grinding, such as accurate dimensions and higher fatigue strength, can be undone in an instant by a simple mistake.
Developing more sophisticated grinding techniques and increasing competence also requires better quality control. This can be due to, for example, the introduction of new materials that will be machined using existing techniques or the deployment of innovative machining techniques, such as 3D printing or heat treatment for microstructural customisation, that will be applied to materials that have been used before.

The ultimate definition of quality is the ability of a product to meet the customer’s expectations.

Research into NDT in the context of quality control increases understanding and awareness of the various techniques and their potential and creates opportunities for using the data in new ways. This is why research is so important for the development of quality and production control. 
New approaches can be discovered by combining innovative and conventional techniques, such as smart computing and modelling, and by increasing cooperation between different scientific disciplines, as was done in the “Smart Manufacturing in an Ecosystem” project. 

Quality control measures process performance

Going forward, a potential trend could be the use of NDT as a means of adjusting and controlling machining parameters in real time instead of focusing on simply testing the standard of the finished article at the end of the production process. This approach aligns well with the principles of sustainable development and resource efficiency. 
The reliability and accuracy of the data based on which the production process is analysed is crucial. This is why only high-quality, measured data should be used to evaluate the standard of finished products. In the case of the “Smart Manufacturing in an Ecosystem” project, the results of NDT were verified by means of laboratory analyses. As long as a sufficiently large sample of data is collected, the absolute quality-control measurements taken during the production process can be verified and a calibration curve drawn.

Minor variations allowed

The ultimate definition of quality is the ability of a product to meet the customer’s expectations. Contemporary quality assurance techniques focus on controlling variation by means of what are known as process capability indices. The modern view is that minor variations in quality are allowed, and the key is for a process to be able to produce output within certain specification limits. This approach attributes variations in the finished product to variation at the individual stages of the production process.

An anomaly in the properties of the material or the machining technique, for example, can therefore escalate during the process and result in the finished product’s being rejected or, in the worst-case scenario, a defective product’s being delivered to a customer, which in turn can cause serious financial and reputational damage and even jeopardise the entire business. Not intervening in these kinds of deviations during the process and only applying quality control procedures to the finished products creates high wastage rates and, above all, a lot of unnecessary work. Integrating NDT into the production process provides an effective solution to this problem. 

What is materials technology?

Different materials such as metals, plastics and ceramics typically have completely different properties. This means that the technologies involved in their production are also fundamentally different.

Materials technology involves selecting materials with the properties that best meet the service requirements of a component as well as maintaining the performance of the materials over the operating life of the component by resisting corrosion, fatigue, temperature and other harmful events.

Materials Science is closely related to materials technology. Materials Science is a multidisciplinary field that connects material properties to the material’s chemical composition, micro-structure and crystal structure.

Non-destructive testing (NDT) is a testing and analysis technique used by industry to evaluate the properties of a material, component, structure or system for characteristic differences or welding defects and discontinuities without causing damage to the original part.

The importance of materials technology usually only becomes clear when something goes wrong.

Case: Non-destructive testing helps to replace an old machine tool 

One way to find new applications for NDT is to use it in connection with tool upgrades as a means of maintaining a consistent performance of the manufacturing process through the transition. The research team involved in the ‘Smart Manufacturing in an Ecosystem’ project applied NDT to a number of real-life cases, one of which sought to maintain consistent quality through the deployment of new manufacturing technology. In this case, NDT served as a means to verify the results of analyses comparing components produced using two different machine tools. The goal was to use the comparative data to establish optimal machining parameters and quality criteria for the new tool. 

Could an innovative smart manufacturing concept be developed by combining NDT measurements and experimental research?
NDT also shows considerable potential in the analysis of material properties beyond the identification of quality deviations, which is what these techniques have conventionally been used for. Modern methods of signal processing and the use of artificial intelligence provide new ways to interpret the results of traditional measurements. The data can then be used in, for example, modelling. Combining other measured material properties with NDT data may lead to the discovery of new, more practical applications of these conventional techniques. This creates new opportunities and potentially a link to the performance and useful life of finished components.