Artificial Intelligence in a Construction Machinery Company
Artificial intelligence technology can be used in a wide variety of areas. In this article, you will learn how AI was used in a mechanical engineering company.
I’ve already written a few posts on this blog about Artificial Intelligence (AI) in sales. Simply a fascinating topic for an old sales hand like me who has worked with several different CRM systems as well as sold AI systems.
For someone in sales, the area of predictive analytics is particularly interesting – an AI is able to predict sales opportunities. That’s why I report on a specific case study below.
Artificial Intelligence in a Mechanical Engineering Company
In this case study, from a company, predictive analytics is used in a completely different way. The customer of mine at that time sold and serviced construction machinery of all kinds. The customers are construction companies as well as rental companies of construction machines. In addition to selling the construction machines, they also maintain and, if necessary, repair them.
The repair shop had an ERP system, a CRM system and another software in use.
The original idea was to use AI with predictive analytics in sales. Then, in discussions, it quickly became apparent that the possible applications could and should be broader. The reasons and opportunities for using AI together with an ERP and/or CRM system have already been discussed in other articles.
Here, however, the opportunity arose to use AI in the area of the workshops as well. After all, predictive analytics is not limited to sales, for AI everything is data and predictions can be derived from data.
The background to this is that for construction machinery, unlike cars or trucks, it is not the kilometers driven that count for maintenance/service, but the operating hours. In addition, components occasionally fail between two maintenance dates. In the worst case, this means stopping the job site until the machine is repaired or replaced, otherwise repair on site. Since today the acceptance dates for construction sites are often subject to contractual penalties, any delay can really cost money. Large projects are usually very tightly budgeted and can run into the deficit in the case of such disruptions.
What can AI Achieve on the Shop Floor?
Always provided that an appropriate database is available for each construction machine, AI can make some predictions with quite high accuracy:
1. Prediction of the Next Maintenance Date.
Given a corresponding database for the customer and the machine, AI is quite capable of predicting the next maintenance date quite accurately. Based on such a prediction, the owner of the construction machine can be contacted and a maintenance date can be suggested. The owner can then check again on the basis of the operating hours counter and confirm the maintenance date or suggest another date.
2. Prediction of Required Spare Parts
Based on the “experience” of the AI, it can predict which spare and wear parts are needed for maintenance. This may well differ from the manufacturer’s recommendations. In such cases it is worth consulting the manufacturer, possibly this problem is already known and there are new, often first internal, recommendations.
3. Predicting which Parts are Likely to Fail between the Upcoming and the Following Maintenance Date.
This can be essential for the owner of a construction machine. As mentioned above, the unplanned failure of a machine can have serious and expensive consequences. As part of preventive maintenance or component replacement, this problem can certainly be avoided. And yes, a very experienced shop foreman can certainly accomplish this. Oddly enough, however, more weight is often attached to the testimony of a computer.
Transfer to other Manufacturing Companies
Of course, this does not only apply to construction machinery, but can also be transferred to other machines, even in production plants this is quite a hot potato. Unplanned downtime is pure poison in any production plant. In projects at another company, I was able to experience that such solutions were successfully implemented there with considerable effort as a “standard solution for maintenance” with SAP BW. The focus at that time was on automotive suppliers.
It is perhaps also interesting that in the area of “white goods” (washing machines, dryers), manufacturers have been working for some time to identify components that fail early. However, early often only means before the warranty expires and a possible goodwill period. In this area, however, it is more a matter of reducing the costs for warranty services.
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Conclusion: AI in the Construction Machinery Distributor
Artificial intelligence technology can be used in a wide variety of areas. For example, it can also help mechanical engineering companies and workshop operations optimize their processes and better tailor their offerings to customers. Of course, the innovative systems will never completely replace a good workshop manager, but they can help them to waste less time on repetitive tasks and thus to use their skills in a more targeted manner.
