However, with the ever-increasing availability of data and a higher level of automation and electrification, production scheduling can no longer be seen as an autonomous solution. Concepts such as Internet-of-Things, smart grids, smart manufacturing, Big Data, Industry 4.0 and software-as-a-service (SaaS) as well as heightened emphasis on enterprise-wide optimization topics increase the pressure to connect to and interact with neighboring solutions and systems.
In most industrial environments, a scheduling solution should be closely connected to the production environment – for instance, to a distributed control system (DCS), manufacturing execution system (MES) or collaborative production management (CPM) system – to automatically obtain all the production and process data necessary for scheduling. A connection to the enterprise resource planning (ERP) system is often essential since production is usually triggered by customer orders entered via an ERP interface. ERP systems are also used for procurement to ensure that the appropriate material and resources are available when called for by the production plan.
For successful scheduling, the following must be known:
- Resource availability – equipment, materials, personnel, utilities, etc.
- Dependencies and rules related to the process steps.
- Current state of production and capacity of the production resources to absorb further production demand.
- Production orders with their due dates and priorities.
- A target for the scheduling.
Some data may change from minute to minute, which highlights the need for connectivity that ensures the schedule is kept up-to-date. In the approach considered here, most of this dynamic type of information has been modeled using the ISA-95 standard, which makes it easy to share and communicate between system components.