Based on modern control technology algorithms, PSIpenta Advanced Planning & Scheduling offers a completely new approach to controlling dynamic production processes. The new function package allows planning and production to be perfectly coordinated, thus ensuring optimum utilisation of machines and employees. The optimised synchronisation of material management and production results in significant reductions in stock levels and shorter mean lead times, and improved delivery capability and adherence to delivery dates.
In many branches of modern industry, production is characterised by fluctuating incoming orders and complex production processes. At the same time, customer requirements are increasing with regard to short delivery times and compliance with promised delivery dates. Faults in individual processes, for example, caused by missing supplier parts or capacity bottlenecks quickly result in backlogs that cannot be cleared, delivery delays and contractual penalties. To remain competitive in this dynamic environment, companies must in particular increase the process speed along the supply chain. This can be achieved by harmonising production processes and cutting mean lead times. This automatically improves production liquidity, reduces stock on-hand and frees tied-up capital. One way of mastering this scenario is to use adaptive planning and control in production processes, in which production automatically compensates for changing conditions.
Conventional, static Enterprise Resource Planning (ERP) systems cannot accomplish the control and optimisation of complex, dynamic manufacturing processes. PSIpenta Advanced Planning & Scheduling is an adaptive system for automatic control. The system takes all planning levels into account to form an up-to-date image of the real situation within the company. The core components of this package are controller components based on modern algorithms. The cascade controllers are used at different levels. They react automatically to faults of various kinds and adjust the entire ERP system dynamically according to definable targets or provide action proposals to decision-makers.
One critical parameter in the production process is the stockpiling of supplier parts. Excessively high warehouse stocks bind too much capital. However, material shortages can quickly lead to delivery delays. In the APS expansion, this problem is resolved by means of self-regulating mechanisms. Theses calculate consumption and demand forecasts. From this data, statistical methods are used to derive correcting variables for the ERP system and to create decision proposals for planning parameters. Sales and the resulting pre-production forecasts are determined at the same time. Anonymous pre-production and procurement and order-related production are logistically separated at a decoupling point. Stocks at this decoupling point are determined dynamically using the sales forecasts and the resulting raw materials consumption forecasts. The system automatically determines the actual purchasing lead times and mean lead times in production. Performance parameters such as downtime and idle time are taken into account when determining mean lead times based on current or future manufacturing resource operating statuses.
A further key component of the APS extension is the determination of the earliest possible feasible delivery date. Delivery deadline determination no longer allows start dates in the past to be used. Stocks and receipts can also be reserved for particular requirements. If reservations already exist, duplicate planning is prevented. For orders with several order lines to be delivered as a complete shipment, all lines are aligned with the latest line and all dependent appointments are shifted. If the start date for procurement or production is fixed, the system identifies all critical assemblies and flags up parts that jeopardise the desired delivery date. It is crucial to plan for limited capacities to ensure that production can proceed without overloading bottleneck units. The resulting order structure is also visualised in a combined tree/Gantt chart. This clearly shows the coverage and deadline situation of all items relevant for the delivery date.
The Dynamic Production Adjustment (DPA) module optimises the order networks with the aim of meeting the prescribed delivery deadlines, taking scarce resources and unforeseen faults into account. The ERP system retains full planning and data sovereignty. This enables faults in purchasing and production to be corrected. Backlog processing prioritises work orders with the aim of meeting confirmed customer appointments under any circumstances. Prioritisation changes the sequence of the whole order network. Transfer times are shortened within the framework of planning options. The resulting order network is visualised and critical paths displayed from a dashboard. A key component of this dashboard is the ability to display complete work order networks as charts or Gantt diagrams. Furthermore, decision-makers receive instructions on how to eliminate faults that the system cannot automatically control.
The Qualicision® technology made by PSI Fuzzy Logik Systeme GmbH supplements the APS package with the option of multi-criteria production sequence optimisation. This involves sequencing orders with regard to variable target criteria. The sequencing is automatically adapted to modified logistical framework conditions or modified optimisation target criteria.
The core modules of the ERP software can be easily supplemented by adding further individual modules: