SGARIEI

Technical Survey to develop a Global Supervisory System (GSS).

  • A technical survey to develop a Global Supervisory System (GSS) —generally a centralized SCADA system— is the exhaustive process of collecting, verifying, and analyzing information in the field (factory, plant, or infrastructure) to understand the current situation, define the needs, and design the architecture of the new monitoring and control system.

  • This process seeks to move from an environment with fragmented information to an integrated and intelligent system.

  • It mainly consists of the following stages and activities:

  • 1. Identification and Definition of Scope (Initial Phase).
  • • SSG Objectives: Define what is to be achieved (cost reduction, time optimization, energy savings, traceability, safety).
  • • Asset Identification: Map all machines, subprocesses and equipment that will be integrated into the supervisory system.
  • 2. Fieldwork (Collection of Technical Information).

  • It is the on-site visit to validate the condition of the equipment.

  • Hardware and Sensor Inventory: Identify brands, models and status of PLCs (Programmable Logic Controllers), RTUs (Remote Terminal Units), sensors and actuators.
  • • Verification of Communication Networks: Analyze the current network infrastructure (Ethernet, Serial RS-485, fiber optics, radios) and verify protocol compatibility (Modbus, Profinet, OPC, etc.).
  • • Evaluation of Electrical and Mechanical Infrastructure: Review control cabinets, power sources and the physical structure of the machines.
  • 3. Process and Data Analysis.
  • • Variable Mapping: Identify which variables need to be monitored in real time (temperatures, flows, pressures, speeds).
  • • Current Control Logic: Understanding how the machinery currently operates and how control commands should be issued from the SSG.
  • • Alarm and Trend Requirements: Define the critical points for real-time alerts and the management of historical data (trends).
  • 4. Definition of System Requirements (Software and Security).
  • • HMI Interface: Define how the visualization will be displayed (graphics, screens, geographical maps if applicable).
  • • Cybersecurity: Evaluate network security to protect the system from external threats, crucial in IoT environments.
  • • Remote Access: Determine the need for monitoring from other departments or locations outside the plant.
  • 5. Survey Deliverables (Technical Report).

  • The final result of the survey is a report or requirements document that includes:

  • • Updated electrical and network plans (As-Built).
  • • List of signals (I/O) to be monitored.
  • • Architecture diagram of the proposed system (servers, clients, networks).
  • • Cost and time estimates for implementation.
  • Advantages of a good lift.

  • A well-executed technical survey ensures that the SCADA/SSG system allows for timely fault detection, resource optimization, and autonomous diagnostics of the production process.


  • DATA:
  • DATA FOR CREATION:

  • To create a Global Supervisory System (GSS), which typically integrates SCADA, MES (Manufacturing Execution Systems), and business intelligence tools, you must collect structured, real-time data from multiple levels of the organization. The goal is to centralize operations, monitor efficiency, and facilitate strategic decision-making.

  • Here are the key data points divided by category:

  • 1. Production and Process Data (Real Time).

  • These are the data obtained directly from sensors and controllers in the plant (PLC/RTU):

  • • Process variables: Temperature, pressure, flow, level, machine speed.
  • • Machine States: In operation, stopped, error, maintenance.
  • • Production Count: Units produced, defective units, production rate (throughput rate).
  • • Cycle Times: Time required to complete a manufacturing cycle.
  • 2. Efficiency and Performance Data (KPIs).

  • Data processed to evaluate performance (MES/SCADA):

  • • OEE (Overall Equipment Effectiveness): Availability, Performance, and Quality.
  • • Downtime: Duration and cause of interruptions.
  • • Energy Consumption: kWh per unit produced, use of water, gas or other resources.
  • 3. Quality and Traceability Data.

  • Data required to ensure compliance with standards:

  • • Quality Parameters: Values ​​measured against technical specifications.
  • • Traceability: Batch numbers, responsible operator, raw materials used.
  • • Alarm Log: History of critical events, violations of security limits.
  • 4. Maintenance and Asset Data.
  • • Vibration and Condition Data: For predictive maintenance.
  • • Operating hours: For usage-based preventive maintenance.
  • 5. Environment and Infrastructure Data.
  • • Geographic Location: Plant data, remote locations (SCADA).
  • • Physical Security Data: Access control to control rooms or process areas.
  • Key Steps for Collection.
  • 1. Standardization: Define a common format for all sites before integration, since local SCADA systems may vary.
  • 2. Connectivity: Use standard protocols (OPC UA, MQTT) to connect industrial IoT devices and PLCs.
  • 3. Security: Implement cybersecurity (firewalls, encryption) in data transfer.
  • 4. Historian: Store historical data in a high-speed "Historian" (more than 100,000 tags/second).

  • The key to a SSG is that information is processed to convert technical data (machine) into business information (productivity).


  • DATA FOR ADMINISTRATION:

  • To effectively manage a Global Supervisory System (GSS), whether in the industrial (SCADA/IIoT) or centralized IT environment, it is crucial to collect structured data that allows for real-time visibility, historical analysis, and incident response.

  • The key data to be collected is divided into four main categories:

  • 1. Infrastructure and Performance Data (Technical Metrics).

  • This data guarantees the availability and health of the physical and virtual components.

  • • Resource utilization: CPU, RAM and storage on servers, controllers (PLC/RTU), and edge devices.
  • • Network health: Bandwidth, latency, packet loss, and connection status between remote sites.
  • • Device status: Uptime, hardware errors, power supply status and temperature.
  • • Application metrics: Database performance, HMI (Human-Machine Interface) response time, and user concurrency.
  • 2. Process and Operation Data (Functional Data).

  • These are the specific data of the operation being monitored, usually centralized from multiple locations.

  • • Real-time field variables: Pressure, temperature, level, flow, speed, motor/valve states.
  • • Events and alarms: Detailed log of critical alarms, warnings, and status changes, with accurate timestamp.
  • • Historical trends: Storing variable values ​​over time for predictive analysis.
  • • Traceability data: Record of operations, production batches, and operator actions.
  • 3. Security and Integrity Data.

  • Essential for protecting the SSG against threats, especially if it is connected to external networks.

  • • Audit logs: Who, what, when and where a change was made to the system.
  • • Access management: Failed login attempts, user authentications, and active permissions.
  • • System integrity: Intrusion detection, integrity of configuration files and firewall status.
  • 4. Context Data and Documentation.
  • • Asset inventory: Map of all connected devices, firmware versions and software.
  • • Network topology: Updated diagrams of the communication structure.
  • • Contingency plans: Data required to execute backup and recovery procedures.
  • Best Practices for Data Collection.
  • • Centralization: Use platforms that allow grouping data from various sources (multisite, hybrid) into a single control panel (Dashboard).
  • • Standardization: Define uniform data formats (label names, timestamps) to ensure comparability between sites.
  • • Automation: Implement agent-based software for continuous and detailed data collection.

  • Proper management of this data allows a shift from reactive supervision to proactive and preventive management.


  • Additional Requirements:
  • List of processes.
  • List of procedures.
  • List of machinery.
  • List of machines.
  • List of systems.
  • List of departments.
  • List of personnel.
  • Customer list.
  • List of roles.
  • List of production lines.
  • List of production plans.
  • List of main faults.
  • List of current problems.
  • List of losses.
  • List of kpi's main departments.
Money transfers.
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