Opportunities with AI and ERP systems

How artificial intelligence is helping SMEs move forward

The rapid development of artificial intelligence (AI) is opening up new opportunities for ERP systems(Enterprise Resource Planning). By combining data from a wide range of business areas with machine learning, processes can not only be optimized – they can also think ahead intelligently and assist in the day-to-day running of a company. Many areas of a company are currently being enriched with artificial intelligence, some of which are described in more detail below.

In fact: When does AI make sense?

Before starting AI projects, it is important to decide:

Does the problem require complex decisions? AI can analyze complex topics that humans cannot grasp
Is the topic or problem solution associated with a high workload?
Are topics associated with a great deal of effort and recurring problems?
Is the required data available?
Questioning the data basis (structured / unstructured)
How os the quality of data?
Is there already a software, that solves the problem?
Does this software work?
If necessary, check where the limits or restrictions are

Below you will find some useful practical application examples:

1. Vendor Grading – Intelligent supplier evaluation:

In purchasing, AI controls the performance and risk assessment of suppliers. Instead of rigid key figures, historical data, delivery times, quality metrics and payment performance are analyzed using machine learning. This creates a dynamic vendor grading system, that:

• Recognize fluctuating delivery reliability at an early stage,
• Correlations identified between delivery behavior and quality,
• provides objective recommendations for supplier decisions.

2. Spare Parts Management – Demand forecast for spare parts

Smoothly functioning spare parts management is essential, especially in production with critical systems. AI-supported requirements planning analyzes installed items, maintenance cycles and machine running times. This enables ERP systems:
• Intelligently readjust minimum stocks,
• submit prognostic orders,
• reduce downtime.
Through real-time synchronization with Infor ION and Data Lake in combination with IoT sensor technology, machine and maintenance data can be automatically evaluated and transferred to material orders. This makes it possible to keep production running more efficiently with predictive maintenance.

3. Predictive Maintenance

Sensors determine data such as temperature, vibration or pressure from production. AI models evaluate this information and recognize patterns that indicate impending machine problems. Infor OS links via IoT components (e.g. OPC UA, REST-APIs) Production data with ERP modules for purchasing, logistics and production – completely automated.
This leads to:
• reduced unplanned downtime,
• optimized inspection cycles,
• proactive material stocks for spare parts

Supplementary image analysis – quality assurance with AI
With the help of the combination of our Fischertechnik model factory, a PLC S7 and image analysis algorithms, we simulate the advantages of improved quality analysis. The cameras photograph the items produced or to be used on the production line in real time – the AI recognizes errors (damages) on photos and marks them automatically & initiates the further QA process.
Result: visual quality control in real time and automated feedback to the ERP instance.

Pilot projects with AI

One successful example is the ongoing pilot project for Demand Planning & Forecasting at one of our long-standing customers from the automotive industry:
AI analyzes sales data and generates automated forecasts – with the aim of significantly improving ERP-based planning processes.
As MJR, we build on solid AI and IoT architectures that enable efficient data flows between sensors and business processes.

Demand Planning

Aim: An AI-generated forecast for specific parts for better, automated demand planning.
Result: In the graph, we see the AI-generated forecast in blue of a specific part based on the historical data and calculated by the AI.
This was compared with the real data in green as soon as it was available. The result was really good and you can see how similar the two curves are.

Partnerships as a success factor

MJR relies on collaborations for specific AI implementations: For example, with Infor for technical platforms such as Infor AI and with research partners from the IoT sector. The demand forecasting pilot project is an example of how ERP & AI expertise is implemented via partner networks.

What are the benefits of AI?

To name just three important benefits of artificial intelligence:

1. Increased efficiency & automation
2. Cost reduction
3. Predictions & predictive intelligence

There are also other important advantages of AI. More about that AI topic on our landingpage about Infor Enterprise AI.