Manufacturing Cell Simulation for Non-Linear Workpiece Scheduling
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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 inefficiencies in factory resource management.
Innovation Solution
A planning system that simulates workpiece processing using a production utilization planner (PUP) core with a simulation and analysis module, which models state machines representing workers, workpiece stations, and AGVs to optimize the order of timed actions and resource allocation, allowing for parallel processing of multiple workpiece configurations in a non-linear sequence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workpieces are processed in a linear sequence through predetermined operations, then the manufacturing process is simple to manage, but factory resources are underutilized and production throughput is low
Solution Approach 1:
The patent implements dynamic workpiece ordering that adapts to real-time factory resource availability and workpiece priorities. The simulation manager continuously evaluates different workpiece sequences and selects optimal orders dynamically, allowing the system to transition from static linear processing to adaptive non-linear processing, thereby improving resource utilization and production throughput
Solution Approach 2:
The patent introduces a new dimension of workpiece ordering by considering multiple factors simultaneously (resource availability, workpiece priority, processing time, queue status) rather than following a single predetermined linear sequence. This multi-dimensional approach enables parallel processing optimization and prevents resource underutilization while managing complexity through systematic evaluation criteria
2Productivity
If factory resources are configured for high-rate linear production of a single program, then production efficiency is high for that program, but resources are underutilized when processing different workpiece configurations
Solution Approach 1:
The patent creates a universal workpiece ordering system that can handle multiple workpiece configurations and programs through the same factory resources. The simulation manager evaluates and optimizes processing sequences for diverse workpiece types, enabling factory resources to adapt to different configurations without dedicated linear sequences for each program, thereby achieving both high throughput and versatility
Solution Approach 2:
The patent changes the parameters of workpiece processing by dynamically adjusting workpiece order based on resource availability, workpiece priority, and processing characteristics. This parameter-based optimization allows the system to efficiently process different workpiece configurations by modifying processing sequences rather than reconfiguring entire production lines, maintaining high productivity across diverse programs
3Ease of manufacture
If workpieces wait for certain operations to be performed before undergoing other operations, then processing sequence is simplified, but resource utilization decreases and costs increase
Solution Approach 1:
The patent applies preliminary action by pre-evaluating multiple workpiece ordering scenarios using simulation before actual production. The simulation manager predicts resource utilization and production outcomes for different workpiece sequences, allowing optimal orders to be determined in advance. This preliminary planning enables non-linear processing that improves resource utilization while maintaining manageable complexity through systematic evaluation
Data Source
AI summary
A production utilization planner (PUP) core for a manufacturing cell has a simulation manager configured to simulate the processing of workpieces arranged in a workpiece order, by performing the steps of: creating an instance of a simulation controller and an instance of a software model of the manufacturing cell, determining a next timed action to be performed by state machines, incrementing the simulation to the next timed action, updating the software model and the simulation controller each time a state machine performs a timed action, and repeating the steps of determining the next timed action, incrementing the simulation, and updating the software model and the simulation controller, until all of the workpieces have been processed. The simulation manager is configured to output a simulated completion time for processing the workpiece order.