Manufacturing Cell Simulation for Workpiece Routing and Throughput
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Solution Overview
Problem
Conventional manufacturing systems face underutilization of resources and low production throughput due to linear processing sequences, especially in low or medium-rate production, leading to high costs and inefficient use of factory resources.
Innovation Solution
A planning system that simulates workpiece processing in a manufacturing cell using a production utilization planner (PUP) core with a simulation and analysis module, which models state machines and work articles to optimize the processing order, allowing for parallel processing of multiple workpiece configurations and non-linear sequences, thereby optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workpieces are processed in a linear sequence on the same equipment, then the processing order is simple and easy to control, but factory resources are underutilized and production throughput is low
Solution Approach 1:
The patent implements dynamic workpiece routing that adapts processing sequences based on real-time resource availability and workpiece priorities. Instead of fixed linear sequences, the system dynamically determines processing paths, allowing resources to be utilized more efficiently while maintaining controllable complexity through automated decision-making algorithms.
Solution Approach 2:
The patent transitions from one-dimensional linear processing to multi-dimensional processing pathways by allowing workpieces to be routed through different sequences of resources based on optimization criteria. This creates a network of possible processing paths rather than a single linear sequence, enabling better resource utilization without proportionally increasing control complexity.
2Productivity
If factory resources are configured for high-rate linear production of a single program, then production speed is high, but resources are underutilized when workpieces must wait for certain operations, leading to low overall throughput
Solution Approach 1:
The patent performs preliminary simulation and analysis of processing sequences to optimize workpiece routing before actual production. By pre-determining optimal paths and identifying potential waiting periods, the system can proactively schedule workpieces to minimize idle time and balance resource utilization, reducing both waiting time and improving overall resource efficiency.
Solution Approach 2:
The patent implements a feedback mechanism where simulation results and actual production data are used to continuously refine processing sequences and resource allocation. This closed-loop system identifies bottlenecks and waiting periods, then adjusts routing decisions to minimize idle time and improve resource utilization over time.
3Productivity
If conventional linear processing is used for low or medium-rate production, then equipment costs can be reduced, but resource underutilization leads to prohibitively high operational costs
Solution Approach 1:
The patent uses virtual simulation models to replicate and analyze processing sequences before implementing them in physical production. By creating digital copies of the manufacturing system and testing different routing scenarios virtually, the company can identify cost-effective processing sequences without requiring complex physical reconfiguration, reducing both equipment and operational costs while maintaining optimized resource utilization.
Data Source
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AI summary
A planning system (100) for simulating the processing of workpieces (452) includes, a simulation manager (220), configured to receive a software model (250) of a manufacturing cell (400), including state machines (256) for performing timed actions on the workpieces (452). The simulation manager (220) is configured to perform the steps of: creating an instance of the software model (250) and a simulation controller (206), determining the next timed action to be performed by the state machines (256), incrementing the simulation to the next timed action, updating the software model (250) and the simulation controller (206) each time a state machines (256) performs a timed action, recording the state transitions associated with the timed action, and repeating the steps of determining the next timed action, incrementing the simulation, and updating the software model (250) and the simulation controller (206), until all of the workpieces (452) have been processed. The simulation manager (220) configured to output a simulated completion time for processing the workpiece order.