Production Asset State Monitoring for Heavy-Vehicle Workflow Control
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Solution Overview
Problem
Existing systems fail to efficiently monitor and manage workflows involving heavy-duty vehicles in complex infrastructure projects, particularly in large-scale construction and mining operations, due to the interdependency of various assets from different manufacturers and varying ages, without requiring extensive asset upgrades.
Innovation Solution
A production asset monitoring system that associates state machines with each asset to automatically detect operating states, aggregates these states into utilization reports, and triggers automated actions based on categorizing states as productive or unproductive, using sensor systems and V2X communication to account for interdependencies among assets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated management systems are implemented to monitor production assets, then productivity and efficiency are improved, but device complexity increases
Solution Approach 1:
The monitoring system is segmented into independent state machines, each associated with a specific production asset. Each state machine autonomously monitors its own asset's operating state, transitions, and productivity metrics. This segmentation allows the system to scale without increasing overall complexity, as each state machine operates independently while contributing to the aggregate production asset utilization report.
Solution Approach 2:
Each production asset serves itself through its associated state machine, which automatically detects operating states, categorizes productivity, and reports data without requiring external intervention. The state machines self-manage the monitoring process, reducing the complexity burden on central system components while maintaining comprehensive oversight.
2Measurement precision
If the system aggregates states of multiple assets into utilization reports, then measurement precision of production efficiency is improved, but loss of time for data processing increases
Solution Approach 1:
State machines perform preliminary categorization of operating states as productive or unproductive at the moment each state is detected, rather than waiting for aggregate analysis. This preliminary action pre-processes data into meaningful categories, enabling rapid aggregation of utilization reports without requiring complex real-time analysis, thus maintaining measurement precision while minimizing time loss.
3Productivity
If the system categorizes operating states as productive or unproductive based on interdependencies, then productivity measurement is improved, but device complexity increases
Solution Approach 1:
State machines incorporate feedback mechanisms that monitor the operating states of other production assets to determine whether a given state should be categorized as productive or unproductive. For example, a truck's stationary state is categorized as productive if feedback indicates it is being loaded by an active excavator, but unproductive if no loading activity is detected. This feedback-based categorization improves productivity measurement accuracy without requiring complex centralized decision-making, as each state machine independently applies the logic based on received feedback.
Data Source
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AI summary
A production asset monitoring system, for automatically monitoring current operating states of one or more production assets, where the production asset monitoring system comprises at least one control unit (130, 160, 170, 230) arranged to associate a respective state machine which each asset in the one or more production assets, where each state machine implements a plurality of operating states, out of which operating states at least one state can be categorized as a productive state and at least one state can be categorized as an unproductive state, where the production asset monitoring system further comprises a sensor system configured to detect a current operating state for each state machine, and where the control unit (130, 160, 170, 230) is configured to aggregate the states of a plurality of assets into a report indicative of production asset utilization.