AI in Mechanical Engineering: Handy Tips for Your Business

In our series of blog articles on artificial intelligence, you've already learnt what role AI plays in mechanical engineering, when algorithms can relieve the strain on service teams, and which three questions companies need to ask themselves before introducing AI. But before you start putting AI theory into practice, we have a few tips to smooth the way for you.
 

Take stock: Are your processes and systems set up for AI?

In order to successfully start using AI, machine constructors first need to check if their processes are already geared up to it or if optimizations are needed. If, for example, your spare parts management workflows are not yet sufficiently interconnected and digitalized, your initial focus should be on creating end-to-end data flows.

Maturity level models like acatech’s “Industrie 4.0 Maturity Index” help businesses with this. Using this model, you can assess not only your internal processes, but also your corporate culture in terms of digitalization. The results show whether you are already using the data you have available effectively. It also forms the basis for a digital roadmap with the ultimate goal being your company becoming an agile organization.

Consider data protection and compliance

Alongside the processes and mindset, existing IT systems and data also need to be checked in terms of their AI maturity, as an accurate database is needed for AI models to make full use of their strengths. Machine manufacturers and operating companies therefore have to thoroughly analyze what data they have, where it comes from, and how it can be used in conjunction with AI.

In this respect it is important that the data be collected seamlessly and correctly, and processed in compliance with GDPR requirements. Data protection and data security must have the highest priority – especially if you want to enrich your data with public information, such as market data on spare parts pricing.

A data protection officer can help you with this. Companies in the EU can also use the Compliance Checker to find out whether their planned use of AI is affected by the new AI Act and whether they need to meet particular specifications.
 

Pilot project: Determine your first application of AI

The next step in getting you on track to introducing AI is selecting a specific use case for your company. When assessing which AI application you should consider for your needs, others factors also play a role in addition to the maturity of your processes and IT systems and the legal conditions.

For example, you need to perform a cost-benefit analysis to systematically assess both the investment costs as well as risks and opportunities of their AI project. What’s more, you should answer the following questions so that you can plan and implement the AI use case as effectively as possible:

• Does the application match your company goals?
• Which specific advantages should the application bring?
• Which needs of which stakeholders must be considered?
• Are you in a position to respond flexibly to changes and make ongoing improvements during the project?
• Should you develop the required AI expertise internally or purchase this from an external party?
• Is the AI solution that you want to use ready for the market and available, and how can you customize it to your specific requirements or retrain it?
• Do you have all the necessary resources – i.e., the knowledge, time, and budget – to successfully implement the AI project?

Once you’ve clarified all these questions and found an appropriate use case for AI, there’s nothing more standing in the way of introducing it. Change management often proves to be a useful tool for the next steps, which are a big change for many companies.
 

Launch the AI project as an organization

Introducing AI in a mechanical engineering company represents a profound change and requires employees to be engaged and the organization to be transformed. Effective change management will help master these tasks and will make the transition to the age of AI as smooth as possible.

An important part of the change process is transparent communication. Change management methods should be used to make the advantages of using AI clear to every individual. This will encourage acceptance and engagement among employees.

A key aspect of this is defining a vision. Change managers must also involve all those affected from the start to listen to them and find out:

• What people’s expectations are of the AI implementation
• What fears they have that need to be overcome
• What training and qualifications the stakeholders need to be able to use AI

Tools like Lewin’s three-stage model or Kotter’s eight-step model can help those responsible take a structured approach to establishing a change like introducing AI in service departments.
 

Three Quanos tips for successfully introducing AI

The easiest way to make sure your AI projects run smoothly is by commissioning the support of experienced partners like Quanos. We develop software solutions for aftersales and service teams in mechanical engineering companies that can have artificial intelligence added to them, allowing them to form the basis for new business models in aftersales and service.

The Quanos experts have the following tips for businesses that want to integrate AI into their processes:

1. Managing expectations: AI can do a lot, but certainly not everything. You should see the technology as an aid for your service team and communicate the solution you're implementing as such.
2. Added value: Define and communicate the specific benefits of the AI application clearly and transparently. To ensure the solution offers added value to its users in practice, it needs to be continuously improved based on feedback from users.
3. Monitoring: AI is not assigned the task of independently controlling machines and equipment, but instead supporting people with operating and maintaining these assets in the best way possible. In order for people to trust the algorithm, AI decisions must be comprehensible. What’s more, monitoring by real people and ethical considerations are indispensable.

You can find these and other recommendations for your AI project in the latest KVD SERVICERADAR “KI im Service”. If you already have specific ideas about using AI in your organization and would like to speak to an expert, don’t hesitate to get in touch.