Computer-implemented method for adapting a first production plan of a first production system for producing a first product
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- ZF FRIEDRICHSHAFEN AG
- Filing Date
- 2026-01-23
- Publication Date
- 2026-08-06
Smart Images
Figure EP2026051691_06082026_PF_FP_ABST
Abstract
Description
[0001] ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0002] Computer-implemented method for adapting an initial production plan of an initial production system to produce an initial product.
[0003] The invention relates to a computer-implemented method for adapting a first production plan of a first production system for producing a first product, a first production system, an overall system comprising the first and a second production system, and a computer program product.
[0004] Globalization has led to a profound transformation in industrial manufacturing, with global supply and value chains playing a central role. These chains are characterized by a complex network of distributed production facilities, suppliers, and distribution centers linked across different countries and continents. Such a structure offers companies significant advantages, such as cost efficiency through regional diversification, access to new markets, and the utilization of local resources. However, it also presents significant challenges, particularly regarding the coordination and control of the various production plans, production processes, and logistics flows.
[0005] A key problem in this context is machine malfunctions and breakdowns, which can have a significant impact on the supply situation throughout the entire supply chain. Such disruptions can lead to considerable delays and interruptions, making production planning extremely difficult. Condition monitoring and predictive maintenance play a crucial role in overcoming these challenges.
[0006] Condition monitoring refers to the continuous monitoring of the condition of machines and equipment during operation. By using sensors and data analysis tools, companies can monitor the condition of their production facilities in real time and detect early signs of wear or malfunctions. This enables predictive maintenance, which minimizes unplanned downtime and extends the service life of the machines. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0007] Production planning in such a complex and dynamic environment requires a sophisticated strategy to optimize delivery times, minimize inventory, and maximize production efficiency. However, this often presents challenges such as a lack of transparency across the entire supply chain, difficulties in predicting market trends, and the complex coordination between different production sites.
[0008] It is an object of the present invention to provide a method, a first production system, an overall system comprising the first and a second production system, and a computer program product that improves at least one or more of the aforementioned disadvantages. In particular, it is an object of the present invention to identify and optimize bottlenecks in production and consumer and / or customer supply in a timely manner in order to be able to react proactively to such problems and minimize disruptions in the supply chain.
[0009] According to a first aspect, the task is solved by a computer-implemented procedure for adapting a first production plan of a first production system to produce a first product. The procedure comprises the following steps:
[0010] - Monitoring the production of the first product and, upon detection of malfunctions in the first production system, outputting a malfunction information characterizing the malfunction;
[0011] - Determining maintenance for the first production system based on the fault information;
[0012] - Determining an impact on an initial production plan of the first production system and a supply chain based on maintenance, wherein the supply chain includes the first production system and at least one of a second production system and an intermediary requesting the first product;
[0013] - Determining provision information for the second production system and / or the intermediary based on the impact, whereby ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0014] The deployment information is characterized by a prediction of the production and deployment of the first product based on the impact;
[0015] - Adjusting the initial production plan of the first production system based on maintenance and the impact on the supply chain, where the adjusted initial production plan is characterized by a forecast of producing and delivering the first product.
[0016] To address the challenges mentioned at the outset, it is proposed to combine production monitoring, particularly in the form of condition monitoring, maintenance planning, particularly in the form of predictive maintenance, and impact assessment, particularly in the form of AI-supported production planning, in a novel way. Firstly, condition monitoring tools can be used to monitor production, especially the production machines of the first production system. These tools can continuously collect operating data from the production machines and detect early malfunctions and / or problems.When such disruptions occur, determining their impact allows for the prediction and simulation of their potential effect on the entire supply chain, thus establishing an effective early warning system for customer supply bottlenecks. This early warning system enables companies to proactively respond to problems and minimize supply chain disruptions.
[0017] The method according to the first aspect is described with respect to the first production system, a second production system, the intermediary, and a warehouse, but is not limited thereto. The person skilled in the art recognizes that the method can be carried out with, for example, more than two production systems, which can communicate with each other and adjust their production plans in accordance with the present disclosure.
[0018] The first production system can be a supplier, and the second production system can be a producer and / or consumer. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0019] Production monitoring can be achieved using condition monitoring equipment. This equipment can utilize a variety of sensors to continuously collect data from the production machines of the primary production system. These sensors can monitor parameters such as temperature, vibration, pressure, and many other operating conditions. The collected data can be analyzed in real time to monitor the current state of the production machines and detect deviations from normal operating conditions. A range of AI-based condition monitoring applications are available for this purpose.
[0020] The malfunction can be a deviation of a production machine of the first production system from a standard and / or target specification for the production machine, for example an increased temperature, excessive play, excessive vibration, etc.
[0021] Maintenance may refer to future maintenance.
[0022] Determining maintenance requirements can be achieved through predictive maintenance.
[0023] The intermediary (broker) can be included in the first production system, the second production system and / or the overall system.
[0024] Furthermore, the first production system, the second production system, and / or the overall system can include at least one warehouse for storing the respective product. The warehouse can be configured to optimize the storage of the respective product based on the provisioning information from the first production system. Two or more warehouses can be provided.
[0025] The first product(s) can be requested from the intermediary and / or the second production system by means of a purchase requisition. The purchase requisition can specify a quantity and / or delivery dates for the provision of the first product. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0026] Adjusting the initial production plan can include optimizing the initial production plan.
[0027] Determining and predicting availability information can continue to be based on the adapted initial production plan.
[0028] Determining the impact can involve simulating the primary production system and the supply chain, at least during maintenance. An impact simulator can be used for this purpose. The simulation can be a mechanism and / or algorithm that simulates and classifies the impact of the disruption on production, the production schedule, and customer supply. The simulation can be a digital twin of the primary production system, an AI component trained from data or using reinforcement learning, or a simplified rule set that assesses the impact of a machine failure. The classification can involve a multi-stage categorization of the impact, particularly regarding supply risks.
[0029] The procedure may include further:
[0030] - Determining a deviation of a production speed of the first production system from a predetermined target production speed based on monitoring production;
[0031] - Determine at least one cause of the deviation and provide deviation information characterizing the deviation and at least one cause.
[0032] Determining maintenance can further be based on deviation information. The target production rate can be predetermined by the user and / or a machine.
[0033] Determining the deviation can be done using an overall equipment effectiveness (OEE) tool for monitoring and optimizing OEE. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0034] The overall equipment effectiveness (OEE) system can continuously collect data from the condition monitoring device(s), including operating times, production speed, and quality data. In addition to real-time data, historical data can also be stored and analyzed to identify long-term trends and patterns. The OEE can monitor the operating times of the production machines and record all planned and unplanned downtime. In the event of downtime, the cause can be identified and categorized (e.g., maintenance, technical malfunctions) to enable targeted improvement measures. All inputs can be entered either automatically or manually by users, particularly experts.The Overall Equipment Effectiveness (OEE) can compare the actual production speed with the target production speed, particularly an ideal target production speed, and identify deviations. By analyzing production speed, bottlenecks and inefficient processes can be identified and optimized. The OEE can be used, in particular, to provide information that can be used for predictive maintenance, including forecasting downtime in the event of machine failure. Several mechanisms can be used to determine downtime. These can include user estimation or automated prediction using machine learning.
[0035] For machine learning, a fault classification tool, particularly in the form of a first AI system for diagnosing machine faults, can be provided. This first AI system is trained and configured to analyze historical data from a CMS system of the first production system in order to classify occurring faults and better assess their impact on production in subsequent steps.
[0036] Furthermore, a downtime forecasting tool, particularly in the form of a second AI system, can be provided to predict the downtime of a production machine. This second AI system is trained and configured to process historical data from production condition monitoring and past maintenance. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0037] to analyze. The second AI system can combine time series analysis and anomaly detection to find patterns and trends in the data. Additionally, a reinforcement learning agent with human feedback is provided to accelerate the learning process and improve the accuracy of the predictions.
[0038] The procedure can further include determining downtime of the first production system based on maintenance, with the determination of the impact being further based on the downtime. Determining the downtime can be done using the downtime forecasting tool.
[0039] The procedure may include further:
[0040] - Determining the service life of wear parts of the first production system based on monitoring production and / or historical data of the first production system;
[0041] - Providing lifetime information characterizing a specific lifespan.
[0042] Maintenance planning can be further based on lifetime information. Lifetime can be determined using a wear part lifetime predictor. This predictor can be a third type of AI system for forecasting the lifetime of wear parts. It analyzes historical condition monitoring data to predict when wear parts will need to be replaced. This information can be used in the spare parts ordering process and for planning and optimizing maintenance work.
[0043] The process can further include producing the first product using the first production system. In particular, production can take place according to the adapted first production plan.
[0044] The process can further include the output of the provisioning information, the initial production plan, the adjusted initial production plan, the maintenance, ZF Friedrichshafen AG file 306141 Friedrichshafen 2025-01-16
[0045] This includes the impact, prediction, simulation, deviation of production speed, target production speed, cause of deviation, downtime and / or lifetime to the user.
[0046] The process may further include issuing the provisioning information to the second production system and / or the intermediary. The intermediary may include means for communicating with the first and second production systems. Furthermore, the intermediary may include means for communicating with the warehouse.
[0047] The steps mentioned so far can be carried out using the first production system.
[0048] The procedure can be further developed to adapt a second production plan for the second production system, wherein the second production system is configured to produce a second product that is at least partially based on the first product. The procedure can further include:
[0049] - Receiving the provisioning information of the first production system; - Determining a capacity to produce the second product based on the provisioning information;
[0050] - Adjusting the second production plan based on the determined capacity.
[0051] The steps of receiving the provisioning information, determining the capacity, and adjusting the second production plan can be performed using the second production system.
[0052] The adjustment can be made in such a way that the deviation from the original second production plan is minimal.
[0053] The determination of capacity can be carried out using a capacity influence determination tool of the first production system, which takes into account the influence of ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0054] Capacity changes of the second production system under planning are simulated and analyzed to identify bottlenecks. If the capacity influence determiner detects a capacity bottleneck in the current plan, this can be communicated to a planning optimization tool of the second production system. This planning optimization tool can be a specialized production planning mechanism that makes as few changes as possible to the production plan to counteract capacity bottlenecks. To achieve minimal change, at least the following objective functions and constraints can be used:
[0055] - Penalizing deviations from the original production plan: The objective function is supplemented with additional (weighted) penalty terms for deviations from the previous solution. Different penalty terms can be provided for deviations at the material level, goods recipient level, customer level, and / or material family level. This weighting ensures more stable planning and thus also stabilizes production and supply chain processes. This is particularly important in the short term.
[0056] - An additional extension could be that the weights of the individual penalty terms can change over the course of the planning horizon. This allows for more precise control of the optimization. Among other things, this means that deviations in stability at the beginning of the planning horizon can be penalized more heavily than at the start.
[0057] - Penalties are imposed for the number of changes compared to the original production plan. This is an additional mechanism to increase the stability of the planning result.
[0058] The process can further include issuing a second demand request to the first production system, where the second demand request characterizes a changed demand based on the adjusted second production plan. The adjustment of the first production plan can then be based on the second demand request. Consequently, an iterative adjustment of the first production plan can occur. Furthermore, communication between the two production systems can be... [ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16]
[0059] or the adjustment of the respective production plan takes place in one or more such loops in order to achieve optimal adaptation.
[0060] The procedure may include further:
[0061] - Determining a supply risk based on the provisioning information of the first production system, the second production plan, the adjusted second production plan, inventory information characterizing the inventory of the second production system for producing the second product and / or customer requests for the second product; - Issuing the supply risk to a user of the second production system.
[0062] Determining and / or reporting the supply risk can be done using a supply risk analysis tool. This tool continuously analyzes all inventory levels (including safety stock), customer demand, and capacity forecasts for the secondary product over time to identify deviations and anomalies. Furthermore, a range of reports are provided to users to monitor the supply situation. This serves as an early warning system for potential shortages.
[0063] The process may further include producing the second product based on the second production plan, in particular the adapted second production plan.
[0064] According to a second aspect, the task is solved by a production system for producing a first product, comprising means for carrying out the process according to the first aspect. This production system can be the first production system.
[0065] The task is solved according to a third aspect by an overall system comprising a first production system for producing a first product according to the second aspect and a second production system for producing a second product, wherein the second production system is a means for executing the ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0066] The process according to the first aspect includes the system. The system can include the warehouse and / or the intermediary. The intermediary can be an entity for coordinating demand requests and supply information. In other words, the intermediary can act as a broker or marketplace. The intermediary can be a device configured to communicate with the production systems and / or the warehouse. The warehouse can further be configured to provide inventory information to at least one of the production systems and / or the intermediary, characterizing the stock level of the first and / or second product.
[0067] Features described with regard to the process according to the first aspect can be described as features of the first production system according to the second aspect and / or of the second production system and vice versa.
[0068] The task is solved according to a fourth aspect by a computer program product comprising instructions which, when the program is executed by a first production system according to the second aspect and / or a third aspect, cause this or these to execute the procedure according to the first aspect.
[0069] Preferred embodiments are explained by way of example with reference to the accompanying figures. These show:
[0070] Fig. 1 shows a schematic representation of a computer-implemented method for adapting a first production plan of a first production system to produce a first product;
[0071] Fig. 2 shows a schematic representation of a relationship between the first production system, a second production system, an intermediary and a warehouse;
[0072] Fig. 3 a schematic detailed representation of the first production system; and ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0073] Fig. 4 shows a schematic detailed representation of the second production system.
[0074] Figure 1 shows a schematic representation of a computer-implemented method 100 for adapting a first production plan of a first production system 200 for producing a first product. The method 100 can be stored as a computer program and saved on a storage medium. Generally, the method 100 can be used in the context of a supply chain comprising at least the first production system 200 and a second production system 300. The second production system 300 requires first products from the first production system 200 to produce a second product. The production of a product requires careful planning and appropriate maintenance of the production machinery. Supply bottlenecks should generally be avoided. Furthermore, optimized production of both the first and second products should be achieved.Optimal production can be understood as resulting in minimal production losses, downtime, storage costs and production errors, as well as maximum consumer satisfaction.
[0075] Procedure 100 comprises monitoring 110 the production of the first product and, upon detection of malfunctions in the production of the first production system 200, outputting 120 malfunction information characterizing the malfunction. The malfunction could, for example, be a production machine temperature that exceeds a predetermined temperature. This could indicate that maintenance is required within a certain timeframe, for instance, because one or more wear parts need to be replaced.
[0076] Accordingly, procedure 100 further includes determining 130 a maintenance date for the first production system 200 based on the fault information. This maintenance may, in particular, take place in the future. Such maintenance may result in a reduced production speed. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0077] Procedure 100 further includes determining 140 an impact on the first production plan and the supply chain based on maintenance, wherein the supply chain comprises the first production system 200 and at least one of the second production system 300 and an intermediary 400, who request the first product by means of an initial demand request. The intermediary 400 may be a broker.
[0078] Furthermore, the procedure 100 includes determining 150 provision information for the second production system 300 and / or the intermediary 400 based on the impact, wherein the provision information is characterized as a forecast of the production and provision of the first product based on the impact. Accordingly, the intermediary 400 and / or the second production system 300 can be informed about the expected changes in delivery quantities and / or delivery times of the first product so that they can react accordingly.
[0079] Procedure 100 further includes an adjustment 160 of the initial production plan of the initial production system 200 based on maintenance and the impact on the supply chain, whereby the adjusted initial production plan is characterized by a forecast of the production and delivery of the initial product. For example, it may be useful to reduce the production speed with regard to future maintenance in order to avoid a supply bottleneck and / or even a production outage.
[0080] The proposed method 100 is described in detail using the following figures as an example.
[0081] Fig. 2 shows a schematic representation of the relationships between the first production system 200, the second production system 300, the intermediary 400, and the warehouse 500, the invention not being limited thereto. The method 100 can also be used only for the relationship between the first production system 200, the intermediary 400, and / or the warehouse 500. Alternatively, the intermediary 400 and / or the warehouse 500 can be omitted. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0082] The first production system 200 communicates directly with the second production system 300.
[0083] Figure 3 shows the second production system 200 in detail. Arrows in Figures 2 to 4 may indicate information exchange or communication. The second production system 200 comprises a condition monitoring device 201, which uses a variety of sensors to continuously acquire data from the production machines of the first production system 200. These sensors monitor parameters such as temperature, vibration, pressure, and many other operating conditions. The collected data is analyzed in real time to monitor the current condition of the production machines and to detect deviations from normal operating conditions. A number of AI-based predictive maintenance applications are available for this purpose, which are described in more detail below: a fault classification device 204, a wear part lifetime prediction device 208, a maintenance work planning device 209, and an anomaly detection device 210.
[0084] The condition monitoring device 201 communicates with a CMS database 202 (Content Management System). The CMS database 202 stores and manages the CMS, production, and quality data and should be well-structured and efficiently organized to ensure fast and reliable data processing.
[0085] Furthermore, the condition monitoring device 201 communicates with an overall equipment effectiveness (OEE) device 203. The OEE device 203 continuously collects data from the condition monitoring device 201, including operating times, production speed, and quality data. In addition to real-time data, historical data is also stored and analyzed to identify long-term trends and patterns. The OEE device 203 monitors the operating times of the production machines and records all planned and unplanned downtime. In the event of downtime, the cause is identified and categorized (e.g., maintenance, technical malfunctions) to enable targeted improvement measures. All entries ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0086] The Overall Equipment Effectiveness (OEE) Mean 203 can be recorded either automatically or manually by experts. It compares the actual production speed with a target production speed, particularly an ideal production speed, and identifies deviations. By analyzing the production speed, bottlenecks and inefficient processes can be identified and optimized. The OEE Mean 203 is used in particular to provide information that can be used for predictive maintenance applications, including predicting downtime in the event of a machine failure. Several mechanisms can be used to determine the downtime. These include expert assessment, automatic prediction using a fault classification Mean 204 and / or a downtime forecasting Mean 205.
[0087] The fault classification tool 204 can be a KL system for diagnosing production machine faults. For this purpose, historical data from the CMS database 202 are analyzed to classify occurring faults and to better assess their impact on production in subsequent steps.
[0088] The downtime forecasting tool 205 can be an AI system for predicting the downtime of a production machine. For this purpose, historical data from the CMS database 202, production data, and past maintenance records are analyzed. The AI system combines time series analysis and anomaly detection to identify patterns and trends in the data. Additionally, a reinforcement learning agent with human feedback is provided to accelerate the learning process and improve the accuracy of the predictions.
[0089] Figure 3 further shows an impact simulator that simulates and classifies the influence of a machine malfunction on production and, in particular, customer supply. The simulation can be either a digital twin of the production machine and / or the production system 200, an AI component trained from data or using reinforcement learning, or a simplified rule set that assesses the impact of a machine failure. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0090] The classification involves a multi-stage categorization of the supply risk.
[0091] Furthermore, Fig. 3 reveals a status user interface 207, which is a user interface with evaluations of the analyses regarding the production system 200 for a user.
[0092] Furthermore, production system 200 includes a wear part lifetime forecasting average 208, which can be a KL system for predicting the lifetime of wear parts of the production machines of the first production system 200. For this purpose, historical data from the CMS database 202 are analyzed to predict when wear parts need to be replaced. This information can be used in the spare parts ordering process and for planning and optimizing maintenance work.
[0093] Production System 200 further includes a Maintenance Work Planning Tool 209, which can be a mechanism for planning maintenance work. This tool uses data from the CMS database, the Wear Part Lifetime Forecasting Tool 208, and Production System 200 to select suitable time periods for maintenance work.
[0094] Furthermore, an anomaly detection device 210 is proposed, which can be a component of AI for anomaly detection. Here, the current and historical data of the CMS database 202 are analyzed to detect deviations from the normal operating state.
[0095] Finally, the production system 200 also includes a production planner 211, which can be a mechanism for production planning. This can be either a manual planning system and / or a fully automated system.
[0096] Using the proposed means of the first production system 200, provisioning information can be provided, which includes a production and ZF Friedrichshafen AG file 306141 Friedrichshafen 2025-01-16
[0097] Provisioning forecast for the provisioning of the first product is characterized. This provisioning information can be provided to the second production system 300. Furthermore, this provisioning information can be used to adjust the first production plan of the first production system.
[0098] Figure 4 shows the second production system 300 in detail. The second production system 300 has requested initial products via a demand request and receives the supply information directly from the first production system 200 or indirectly via the intermediary 400. The intermediary 400 can be a computer-based mechanism for optimizing the distribution of demand, supplier production capacities, and inventory. The warehouse 500 can be an optional optimization component for coordinating inventory and orders in one or more warehouses. These can serve as buffers for supplying consumers.
[0099] The second production system 300 includes a capacity influence determination tool 301, which can be a mechanism that simulates and analyzes the influence of capacity changes of the production system to be planned, here the second production system 300, in order to identify bottlenecks. If the capacity influence determination tool 301 detects a capacity bottleneck in the current second production plan of the second production system, a planning optimization tool 302 is triggered.
[0100] Planning Optimization Tool 302 can be a specialized production planning mechanism that makes as few changes as possible to the secondary production plan to counteract capacity bottlenecks. Planning Optimization Tool 302 can solve an optimization problem that may have one or more of the following objective functions and constraints:
[0101] - Penalizing deviations from the original plan: for this purpose, the objective function is supplemented with additional (weighted) penalty terms for deviations from the previous solution. Different penalty terms can be used for deviations at the material level, the goods recipient level, ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0102] This information can be provided at the customer level or material family level. This weighting ensures more stable planning and thus also stabilizes production and supply chain processes. This is particularly important in the short term.
[0103] An additional feature is that the weights of the individual penalty terms can change over the course of the planning horizon. This allows for more precise control of the optimization. Among other things, this means that deviations in stability at the beginning of the planning horizon can be penalized more heavily than at the start.
[0104] - Penalties are imposed for the number of changes compared to the original plan. This is an additional mechanism to increase the stability of the planning outcome.
[0105] The second production system 300 further includes a risk analysis tool 303, which can be used to analyze supply risk. Here, all inventory levels (including safety stock), customer demands, and capacity forecasts for components are continuously analyzed over time to detect deviations and anomalies. Furthermore, a range of reports are provided to users to monitor the supply situation. This constitutes an early warning system for bottlenecks.
[0106] Based on the adjusted production plan of the second production system 300, a second demand request can be created and sent to the first production system 200 to enable optimal production for the first and second production systems 200 and 300.
[0107] The proposed method 100, as well as the first and second production systems 200 and 300, achieve the following technical advantages:
[0108] - Early fault detection: Condition monitoring devices 201 detect malfunctions and problems in production machines early, before they lead to major failures. This enables proactive maintenance and repairs, thereby minimizing unplanned downtime. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0109] - Effective early warning system: By simulating the impact of disruptions on the entire supply chain, companies can identify potential problems early and take countermeasures. This increases the resilience of the supply chain and reduces the risk of production interruptions.
[0110] - Optimized production planning: AI-supported production planning, in particular, enables dynamic adjustment of production plans to current conditions. This leads to more efficient use of resources and better responsiveness to unforeseen events.
[0111] - Cost efficiency: By reducing downtime and optimizing production processes, companies can save costs. More efficient processes and fewer unplanned shutdowns contribute to lower operating costs.
[0112] - Increased transparency: Procedure 100 provides a better overview of the condition of production machinery and supply chain processes. This facilitates decision-making and improves coordination between different production sites and suppliers.
[0113] - Improved product quality: Continuous monitoring and optimization of production processes improves the quality of manufactured products. This leads to higher customer satisfaction and strengthens the company's competitiveness.
[0114] Sustainability: More efficient production processes and better resource utilization contribute to reducing the ecological footprint. This enables companies to operate more sustainably and achieve their environmental goals. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16
[0115] Reference mark
[0116] 100 Computer-implemented methods for adapting an initial production plan of an initial production system to produce an initial product
[0117] 110 Monitoring the production of the first product
[0118] 120 Issuing a fault message
[0119] 130 Determining a maintenance schedule
[0120] 140 Determining an effect
[0121] 150 Determining provisioning information
[0122] 160 Adjusting the initial production plan
[0123] 200 first production system
[0124] 201 Condition monitoring equipment
[0125] 202 CMS database
[0126] 203 Overall Equipment Effectiveness Means
[0127] 204 error classification tools
[0128] 205 Downtime Forecasting Tool
[0129] 206 Impact Simulator
[0130] 207 Status User Interface
[0131] 208 Wear part lifetime forecast average
[0132] 209 Maintenance work planning tools
[0133] 210 anomaly detection devices
[0134] 211 Production Planners
[0135] 300 second production system
[0136] 301 Capacity Impact Determinant
[0137] 302 Planning optimization tools
[0138] 303 Risk analysis tools
[0139] 400 intermediaries
[0140] 500 bearings
Claims
ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16 Patent claims 1. Computer-implemented method (100) for adapting a first production plan of a first production system (200) for producing a first product, comprising the steps: Monitoring (110) the production of the first product and, upon detection of disturbances in the first production system (200), outputting (120) disturbance information characterizing the disturbance; Determine (130) a maintenance of the first production system (200) based on the fault information; Determine (140) an impact on the first production plan and a supply chain based on maintenance, wherein the supply chain includes the first production system (200) and at least one of a second production system (300) and an intermediary (400) requesting the first product by means of an initial demand request; Determine (150) provisioning information for the second production system and / or the intermediary based on the impact, wherein the provisioning information is characterized by a prediction of the production and provision of the first product based on the impact; Adjusting (160) the initial production plan of the initial production system (200) based on maintenance and the impact on the supply chain, wherein the adjusted initial production plan is characterized by a forecast of producing and delivering the initial product.
2. Method (100) according to claim 1 , where adjusting the initial production plan includes optimizing the initial production plan.
3. Method (100) according to one of claims 1 or 2, Determining and predicting availability information continue to be based on the adjusted initial production plan. ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16 4. Method (100) according to any one of the preceding claims, Determining the impact involves simulating the initial production system and the supply chain, at least during maintenance.
5. Method (100) according to any one of the preceding claims, further comprising: Determining a deviation of a production speed of the first production system (200) from a predetermined target production speed based on monitoring production; Determine at least one cause of the deviation and provide deviation information characterizing the deviation and at least one cause. where determining (130) the maintenance is further based on the deviation information.
6. Method (100) according to any one of the preceding claims, further comprising: Determining downtime of the first production system based on maintenance, where determining (140) the impact is further based on downtime.
7. Method (100) according to any one of the preceding claims, further comprising: Determining the lifetime of wear parts of the first production system (200) based on monitoring production and / or historical data of the first production system (200); Providing lifetime information characterizing a specific lifespan, where determining maintenance (130) is still based on lifetime information.
8. Method (100) according to any one of the preceding claims, further comprising: Output of the provisioning information to the second production system (300) and / or the intermediary (400). ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16 9. Method (100) according to claim 8, wherein the method is further configured to adapt a second production plan of the second production system (300), wherein the second production system (300) is configured to produce a second product based at least partially on the first product, the method (100) further comprising: Receiving the provisioning information of the first production system (200); Determining a capacity to produce the second product based on the provisioning information; Adjusting the second production plan based on the determined capacity.
10. Method (100) according to claim 9, the adjustment is made in such a way that the deviation from the original second production plan is minimal.
11. Method (100) according to claim 9 or 10, further comprising: Issuing a second demand request to the first production system (200), wherein the second demand request characterizes a changed demand based on the adjusted second production plan, where the adjustment of the first production plan is still based on the second demand request.
12. Method (100) according to any one of claims 8 to 11, further comprising: Determining a supply risk based on the provision information of the first production system (200), the second production plan (300), the adjusted second production plan, inventory information characterizing the inventory of the second production system (300) for producing the second product and / or customer requests for the second product; Transfer of supply risk to a user of the second production system (300). ZF Friedrichshafen AG File 306141 Friedrichshafen 2025-01-16 13. Production system (200) for producing a first product, comprising means (201-211) for carrying out the method (100) according to any one of claims 1 to 8.
14. Overall system comprising a first production system (200) for producing a first product according to claim 13 and a second production system (300) for producing a second product, wherein the second production system (300) comprises means (301-303) for carrying out the method (100) according to any one of claims 1 to 12.
15. Computer program product comprising instructions which, when the program is executed by a first production system (200) according to claim 13 and / or a total system according to claim 14, cause the latter to execute the method (100) according to any one of claims 1 to 12.