For manufacturing companies, greater flexibility and shorter delivery times with simultaneously increased delivery reliability are more important success factors for asserting themselves in a highly competitive market. In production, transparency and responsiveness are developing into decisive target values. The networking of production through the Internet of Things and Services (IoTS) and cloud computing enables these objectives to be met even in highly complex supply chains.
The fourth industrial revolution has long ceased to be a vision and is becoming increasingly integrated into the reality of many companies. The link between the real and the digital world is the decisive element here. Dynamic management of complex systems is made possible by the real-time, intelligent, horizontal and vertical networking of machines, people, objects and IT systems. In production in particular, the immediate provision and processing of information means that faults can be detected more quickly and their effects reduced to a minimum.
Why is "adaptive detailed planning" so relevant in your company? Innovative technologies, such as those provided by SAP Leonardo, create greater information accuracy and transparency across the supply chain. This increases the ability to react in the planning environment. Deviations from the production plan can be identified at an early stage and taken into account in adaptive planning. Disruption management adapted to the company and processes enables short-term measures to be taken to minimize the effects of disruptions.
In the spatial, temporal and quantitative planning of activities in the production area, production planning is based on a defined production program, available workstations and punctual deliveries from suppliers. Especially in long supply chains, these conditions can change constantly. This leads to deviations between the planning and production levels.
Conventional production planning tools rely on the top-down approach. This assumes a fixed production program, available resources and punctual component deliveries. Extensive supply chains are particularly susceptible to disruptions such as machine breakdowns, tool breakages, staff shortages, delivery delays or short-term changes in demand. Efficient disruption management is necessary to minimize the effects of these disruptive events. If disruptions can no longer be avoided, they must be identified immediately and classified in terms of their impact on the production plan. After assessing the significance of a disruption, appropriate measures can be derived to minimize the impact of disruptions. In this way, the virtual world is adapted to the real conditions.
Is your goal to align detailed production planning with actual environmental information from all areas of your company? Then CONSILIO's team of experts is the right partner to have at your side.
"Smart things - machines, products, containers, etc. equipped with sensors - provide information via the IoT Cloud Service. Data is collected and analyzed there. A previously defined fault management system tailored to the company sends planning-relevant events to the backend. In detailed planning, heuristics and optimizer-based methods are used to reschedule or reschedule.
Comprehensive networking through digitalization across all value-added partners creates completely new possibilities for production regulation and control. Intelligent products equipped with RFID chips and sensors create greater transparency. Detailed information on stock levels, goods flows and the status of production is available at all times.
In addition to a platform for developing your own applications, the SAP Cloud Platform (SCP) also offers a wide range of services that are ready for integration. The IoT service models a digital twin for the connected devices and machines. This enables communication. Each individual device is assigned a device type which, in combination with the message type, determines the parameters to be transmitted. The data transmission itself is carried out using the Message Management Service. The transmitted information can also be analyzed in the cloud.
Alternatively, the machines can also be connected directly to the CONSILIO web service and analyzed in the backend. If deviations from the plan are detected, these can be processed directly in the backend system and integrated as planning restrictions.
Another important aspect of implementing adaptive production planning in your company is integrating the detailed production planning module into the SAP S/4HANA Business Suite. By reducing the number of interfaces, processes can be run more efficiently. The PP/DS module offers a variety of heuristic and optimizer-based procedures that can be used effectively in the context of adaptive detailed production planning.
CONSILIO has tested these procedures and analyzed their strengths and weaknesses. Both are executed without significant delays. There are serious differences in the process runtime. While heuristics-based rescheduling requires only a few seconds due to the small number of objects to be adjusted, the speed of the optimizer-based approach is limited by the maximum runtime. On the other hand, the latter delivers a result optimized for the short-term horizon, while heuristics only ensure feasibility.
This means that a wide range of planning restrictions can be taken into account when rescheduling as a result of a deviation from the plan. Thanks to the powerful HANA database, feasible and optimized production plans can be generated within a very short time. Production instructions that do not take into account the current status at the production level due to outdated information are now a thing of the past.
This master thesis deals with the question of how disruptive events within a supply chain can be taken into account in near-real time by adaptive detailed production planning within the framework of an APS system in order to minimize the effects on production targets, especially on adherence to delivery dates and resource utilization. To answer this question, in addition to Internet of Things (IoT) and cloud computing, an approach for predictive-reactive production control through new or rescheduling as well as the concept of detailed production planning as a control loop are used.