8.6 KiB
MinerOps
Operational Intelligence for Mining
Mission
MinerOps combines real-time operational awareness, durable asset identity, repair intelligence, spatial visualization, historical analytics, and actionable context in one self-hosted platform. It helps operators understand what is happening, why it is happening, and what should happen next.
Product Vision
MinerOps transforms operational data into useful decisions across the full lifecycle of a mining operation. It connects live conditions to the durable identity, location, repair history, component context, and prior performance of the equipment involved. The goal is practical operational clarity: observations should lead to explanations, priorities, and safe next actions.
The current product is an early-stage operational application with foundations for authentication, inventory and identity, telemetry, locations, repair workflows, control-board replacement, repair-part records, and a minimal tracked component registry. These foundations do not yet constitute the complete vision. Advanced spatial workflows, comparative time-series analytics, generalized component movement and genealogy, donor workflows, and decision support remain future direction unless an approved implementation task establishes otherwise.
Product Pillars
1. Operations
Operations turns live fleet state into an understandable work queue. It covers health, availability, alerts, safe controls, and prioritized next actions—for example, identifying miners that are offline, overheating, unstable, or awaiting intervention.
2. Assets
Assets gives every miner and meaningful tracked component a durable identity independent of mutable network addresses, hardware assignments, and physical location. Examples include Asset IDs, lifecycle state, MAC history, component identity, and movement history.
3. Repairs
Repairs preserves the context and outcome of maintenance work. Examples include repair episodes, ordered timelines, diagnostics, parts used, control-board replacement, testing, and return-to-service decisions.
4. Spatial Intelligence
Spatial Intelligence explains operations through the physical structure of the mine. It connects sites, rooms, racks, shelves, miners, work areas, and live status so operators can see where problems and opportunities are concentrated.
5. Analytics
Analytics explains performance and reliability over time. It compares actual behavior with expectations and relates changes to operational events—for example, power and hashrate trends, thermal hotspots, recurring failures, and repair outcomes.
Core Principles
Technician First
Design common workflows for the people doing the work, with fast lookup, clear context, and minimal avoidable data entry at the point of action.
Operational Awareness
Show current condition, scope, urgency, and impact so operators can distinguish normal variation, intended downtime, and actionable problems.
Durable Identity
Follow miners and tracked components through network changes, movement, repair, transfer, and retirement without redefining them by mutable attributes.
Immutable History
Preserve meaningful operational facts. Corrections append or void explicitly; they do not silently rewrite or delete the past.
Maps Explain Location
Use spatial views to reveal where assets, work, capacity, and operational risk are concentrated.
Graphs Explain Trends
Use synchronized time-series views to make change, correlation, and divergence from expected performance visible.
Timelines Explain History
Use ordered events to show what happened, when it happened, and who or what was responsible.
Tables Explain Detail
Use searchable, sortable tables when operators need precise values, comparisons, and bulk review.
Search Everything
Make durable identities, network observations, serials, locations, repairs, and components discoverable from a consistent search experience.
Live by Default
Present the freshest trustworthy operational state by default while making its timestamp, source, and staleness clear.
Explain, Do Not Merely Report
Connect symptoms to history, location, related events, and likely next checks instead of displaying isolated measurements.
Database-Backed Integrity
Enforce critical identity, history, ownership, and concurrency invariants in PostgreSQL as well as in application workflows.
Progressive Complexity
Keep basic inventory, monitoring, and repair work useful without requiring every advanced model, while allowing richer structure as operational needs grow.
Real Operational Problems Before Interesting Technology
Adopt technology only when it makes mining operations safer, clearer, faster, or more reliable.
Mine Map
The Mine Map is a primary operational interface, not an optional visualization. It should connect physical layout to live condition, work state, and historical context so an operator can move from a site-wide pattern to the relevant group or miner.
The current application includes a location map and operational overlays. The longer-term Mine Map should support production rooms, racks, shelves, miners, repair benches, burn-in racks, quarantine, donor storage, component storage, status overlays, temperature and efficiency hotspots, and drill-down into miners and groups. Capabilities beyond the implemented location foundations are future direction, not present functionality.
Analytics
Time-series analytics is a core MinerOps capability. It should cover site and miner power, hashrate, efficiency, temperature, availability, and expected versus actual performance. Graphs should use synchronized event annotations so repairs, moves, component changes, configuration changes, and operational events can be evaluated against measured behavior.
Operators should be able to compare rooms, racks, models, firmware versions, or selected miners over the same interval. Current telemetry collection and status views are foundations for this direction; the complete comparative analytics experience is not yet implemented.
Component and Donor Workflows
MinerOps must support the real-world practice of combining working components from multiple failed miners to return one miner to service. Meaningful physical components need durable identity, transfer history, donor-miner context, component genealogy, and explicit movement through repair benches and storage. No workflow should silently recreate a component or lose its prior ownership, installation, condition, or repair history.
The current minimal component registry, repair-part snapshots, and authoritative control-board replacement history are foundations only. Generalized component installation, transfer, location, donor, and genealogy workflows remain future direction.
Success Criteria
A technician should quickly answer:
- What is broken?
- Where is it?
- Why might it be failing?
- What repair work has already occurred?
- What parts or components were used?
- Did this component come from another miner?
- What should I do next?
A manager should quickly answer:
- Is the site healthy?
- Where are the largest operational risks?
- Where are power, hashrate, or temperature anomalies?
- Which repairs are delayed?
- Which rooms, racks, models, or components fail most often?
- Are reliability and efficiency improving?
What MinerOps Is
MinerOps is being built as an operational intelligence platform that integrates monitoring, repair workflows, durable asset history, component history, spatial visualization, analytics, and operational context. It is the shared operational record that connects a live observation to the physical asset, its location, its history, and the decision it informs.
What MinerOps Is Not
MinerOps is not intended to become a generic ERP, an accounting platform, a full purchasing system, a general warehouse-management system, or a replacement for operator judgment. Those systems may integrate with MinerOps later when doing so improves operational context without changing MinerOps's core purpose.
Long-Term Direction
Potential long-term directions include historical map playback, predictive maintenance, failure correlation, component genealogy, fleet optimization, AI-assisted investigation, and decision support. These are areas for evaluation, not delivery commitments. AI should organize evidence, surface relationships, and suggest investigations in support of operator judgment; it should not replace that judgment.
Final Guiding Principle
Every feature should solve a real operational problem experienced by technicians, operators, or managers. Operational clarity takes priority over technical novelty.