Machine Axis Sizing and Production Scheduling for Lower Energy Cost
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Solution Overview
Problem
Industrial automation systems face high energy costs due to inefficient design and operation phases, particularly in drive/actuator sizing and production rate scheduling, which are exacerbated by varying time-of-day and tiered energy costs, leading to increased energy consumption and costs.
Innovation Solution
A computer-readable medium and method that generates axis solutions for actuators, drives, and load transmission components based on a model, optimizing energy consumption by simulating enhanced production rate schedules that minimize energy costs while meeting production objectives, using a processor to receive inputs such as motion profiles, mechanical designs, time-of-day energy costs, and desired production rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If drive/actuator sizing solution is selected during design phase without energy optimization, then machine can achieve desired production rate, but energy consumption increases during operation phase
Solution Approach 1:
The system performs energy optimization calculations and selects optimal drive/actuator sizing solutions during the design phase before the machine is built. This preliminary action prevents energy inefficiency from occurring during operation, rather than trying to correct it later when the machine is already consuming excessive energy
Solution Approach 2:
The system uses energy consumption data and cost information as feedback to evaluate different drive/actuator sizing options during design phase, selecting the configuration that minimizes energy usage while maintaining required production rates
2Productivity
If machine application code follows set production rate schedules without energy cost consideration, then production targets are met, but energy costs increase due to time-of-day and tiered energy costs
Solution Approach 1:
The system dynamically adjusts production rate schedules based on real-time energy cost data, time-of-day variations, and tiered energy cost structures. Instead of following fixed schedules, the machine operation code adapts production rates to exploit lower energy cost periods while still meeting overall production targets
Solution Approach 2:
The system changes operational parameters (production rates, scheduling) based on energy cost conditions. When energy costs are high, the system adjusts production parameters to reduce consumption; when costs are low, it increases production, thereby optimizing the balance between productivity and energy cost
3Productivity
If energy usage exceeds specific threshold in tiered energy cost regions, then production continues at current rate, but subsequent tiered energy costs are applied increasing total cost
Solution Approach 1:
The system continuously monitors energy consumption against tiered cost thresholds and uses this feedback to adjust production rates before exceeding costly thresholds. This prevents the machine from operating in higher cost tiers by proactively managing consumption levels
Data Source
Figure 1
Figure 2A~2B
Figure 3
AI summary
In one embodiment, a tangible, non-transitory computer readable medium stores instructions that, when executed by a processor, are configured to cause the processor to receive a first set of inputs including a motion profile of a machine, a mechanical design of the machine, or both, generate a number of axis solutions for one or more actuators, drives, and load transmission components based on a model using the first set of inputs, generate a production rate versus amount of energy consumed per part curve for each of the number of axis solutions, and display the production rate versus amount of energy consumed per part curves for each of the number of axis solutions. One of the curves includes a point on the curve indicative of a lowest amount of energy consumed for a desired production rate range.