zwitschi
04d7f202b6
- Introduced a new document outlining UI structure, reusable template components, CSS variable conventions, and per-page data/actions for the CalMiner application. - Removed outdated idempotency audit and logging audit documents as they are no longer relevant. - Updated quickstart guide to streamline developer setup instructions and link to relevant documentation. - Created a roadmap document detailing scenario enhancements and data management strategies. - Deleted the seed data plan document to consolidate information into the setup process. - Refactored setup_database.py for improved logging and error handling during database setup and migration processes.
2.5 KiB
Roadmap
Overview
Scenario Enhancements
For each scenario, the goal is to evaluate financial viability, operational efficiency, and risk factors associated with the mining project. This data is used to perform calculations, generate reports, and visualize results through charts and dashboards, enabling users to make informed decisions based on comprehensive analysis.
Scenario & Data Management
Scenarios are the core organizational unit within CalMiner, allowing users to create, manage, and analyze different mining project configurations. Each scenario encapsulates a unique set of parameters and data inputs that define the mining operation being modeled.
Scenario Creation
Users can create new scenarios by providing a unique name and description. The system will generate a new scenario with default parameters, which can be customized later.
Scenario Management
Users can manage existing scenarios by modifying their parameters, adding new data inputs, or deleting them as needed.
Data Inputs
Users can define and manage various data inputs for each scenario, including:
- Geological Data: Input data related to the geological characteristics of the mining site.
- Operational Parameters: Define parameters such as mining methods, equipment specifications, and workforce details.
- Financial Data: Input cost structures, revenue models, and financial assumptions.
- Environmental Data: Include data related to environmental impact, regulations, and sustainability practices.
- Technical Data: Specify technical parameters such as ore grades, recovery rates, and processing methods.
- Social Data: Incorporate social impact assessments, community engagement plans, and stakeholder analysis.
- Regulatory Data: Include data related to legal and regulatory requirements, permits, and compliance measures.
- Market Data: Input market conditions, commodity prices, and economic indicators that may affect the mining operation.
- Risk Data: Define risk factors, probabilities, and mitigation strategies for the mining project.
- Logistical Data: Include data related to transportation, supply chain management, and infrastructure requirements.
- Maintenance Data: Input maintenance schedules, costs, and equipment reliability metrics.
- Human Resources Data: Define workforce requirements, training programs, and labor costs.
- Health and Safety Data: Include data related to workplace safety protocols, incident rates, and health programs.