Classic ERPs don't provide enough details
Since the classic enterprise resource planning (ERP) systems show too little detail for medium- and long-term production optimization, VDI recommends adding manufacturing execution systems (MES). These "offer a useful functional addition for just-in-time planning and controlling of all manufacturing processes, to ensure process transparency, and to map the flow of materials and information within the supply chain."
At the center of the supply chain
The MES is thus placed at the center of manufacturing companies' supply chain. Its tasks begin in the "PLAN" phase, i.e. the detailed planning and control of production. In the "MAKE" phase, it supports the actual production process with all the necessary steps. In addition, an MES also offers functions for the "CONTROL" area (called "performance analysis" in the VDI 5600 guideline): Actual data from production is collected, analyzed, and converted into information to support the continuous improvement of processes.
According to the VDI 5600 guideline, an MES takes on the following tasks:
- Worklist management
- Defining order types
- Creating reference objects for production
The current challenges for order management arise from the increasing demands of customers in the B2C and increasingly also in the B2B area for a high number of variants and even the demand for increasingly individual products, often as one-offs.
Detailed planning and control
- Detailed worklist planning
- Sequencing and sorting
- Fault management
The same challenges mentioned above order management occur for detailed planning and control, namely an ever-increasing number of variants and the goal of one-off production runs.
- Operator guidance
- Integration layer
The challenge for information management is to digitalize all the processes to create paperless production processes and to ensure that they and the IT run in sync.
- Test equipment management and connection
- Inspection during production
- KAIZEN with predictive quality
The aim of quality management is scrap-free production and the possibility of anticipating and avoiding errors (predictive quality). Today it is important to digitalize the quality assurance process using digital twins.
- Shift and personnel scheduling
- Personnel management including working time accounts and qualifications matrices
- Staff time recording
Personnel management, digitalized as far as possible, should help ensure the optimal deployment of workers, create transparency, and avoid disruptions or rectify them as quickly as possible.
- Supplies management
- Consideration in the detailed planning
- Monitoring of measurement points
- Maintenance and repair
The greatest challenges in equipment management lie in preventive maintenance and in creating full transparency with the help of the overall equipment effectiveness (OEE), a parameter that helps detect and counteract the wasting of resources effectively.
Operational data recording
- order data (quantities, types of services)
- Personnel data
- Quality data
- Process data
The use of operational data should lead to a paperless factory: digital processes should be used to enable data reporting to take place in real time. Process data should also flow into the analyses.
- irculating inventory, WIP inventory (lot, batch, serial)
- Material flow controls
- Production supply and disposal
Here it is important to make decisions so that the right material is available in the right quantity and quality in the right place at the right time. Is it best to do this in individual cases with a pull or push control? An alert monitor should warn of malfunctions and thus enable those responsible to take countermeasures in good time.
- KPIs, benchmarking
- Real-time visualizations (e.g. with the Andon visual management method)
- Predictive and prescriptive analyses
The challenges in this area can be summarized as follows:
Create transparency in order to be able to control and regulate the processes on a constantly updated, complete database. This enables companies to answer the following questions that are central to efficient production:
- What’s happening right now? (Visualization)
- Why did it happen? (Transparency)
- What is going to happen? (Control)
- How do I make everything work? (Regulation)