Industrial Machine Power Scheduling for Suspension Time Allocation
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Solution Overview
Problem
Industrial machines in manufacturing sites face power shortages due to excessive power consumption, making it difficult to align the timing of power-consuming and power-regenerating operations, leading to increased energy usage and heat generation.
Innovation Solution
A management device that allocates a preset total suspension time to industrial machines, using machine learning to determine optimal operation timing adjustments based on power consumption data, thereby minimizing average power consumption by synchronizing power consumption and regeneration across machines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple industrial machines operate independently based on individual control programs, then each machine can perform its designated operations, but the total power consumption exceeds the power supply capacity causing power shortages
Solution Approach 1:
The patent combines the control of multiple industrial machines under a single management device that coordinates their operations. By merging the scheduling function, the system manages power consumption collectively across all machines, enabling them to operate within the power supply capacity while maintaining overall productivity.
Solution Approach 2:
The management device dynamically adjusts the operation timing of each industrial machine based on real-time power consumption patterns and supply capacity. This dynamic scheduling allows machines to be operated during periods when power is available, preventing power shortages while maintaining production goals.
2Loss of energy
If the start timing of operations for each industrial machine is shifted to reduce total average power consumption, then power usage is optimized, but it becomes difficult to determine how to shift timing for each machine
Solution Approach 1:
The management device implements feedback mechanisms that monitor power consumption patterns and operation timing of each machine. Based on this feedback, the system automatically adjusts the start timing of operations to optimize power usage, reducing the need for complex manual scheduling while achieving energy efficiency goals.
Solution Approach 2:
The system enables each industrial machine to autonomously adjust its operation timing based on instructions from the management device. This self-service approach allows machines to independently coordinate their operations for power optimization without requiring complex centralized control logic for each individual machine.
3Loss of energy
If power-consuming and power-regenerating operations are aligned in timing, then regenerative power can be utilized, but it is difficult to align the timing of these operations across multiple machines
Solution Approach 1:
The management device acts as an intermediary that coordinates between power-consuming and power-regenerating operations across multiple machines. It identifies opportunities for regenerative power utilization and schedules operations to maximize this energy recovery, simplifying the timing alignment process while improving energy efficiency.
Data Source
AI summary
A management device includes a data acquisition unit that collects data related to power consumption supplied to a plurality of industrial machines from at least a power supply facility, a preprocessing unit that creates power consumption data based on the collected data, a decision making unit that determines a behavior of allocating a predetermined total suspension time to the plurality of industrial machines with respect to a current state of power consumption by the plurality of industrial machines with reference to a learning model associating a value of a behavior of allocating the predetermined total suspension time to the plurality of industrial machines with a state of power consumption by the plurality of industrial machines based on power consumption data, and a suspension time allocation unit that allocates the suspension time to the plurality of industrial machines.