Planning, process and production technicians

reviews and analyses production data

AI analytics platforms (e.g., Power BI Copilot, Tableau AI) can automatically analyse production data, identify trends, and generate reports with minimal human input.

supports implementation of plans of sequence of operations and completion dates for each phase of production or processing

AI scheduling tools (e.g., Preactor, Siemens Opcenter) can generate and optimise production sequences and timelines, significantly reducing manual planning effort.

plans the cost impact and staff resources for projects

AI-powered project management and resource planning tools (e.g., Microsoft Copilot in Project, Smartsheet AI) can model cost scenarios and resource allocation, though human validation is essential.

works with engineers on production control methods to monitor operational efficiency and helps to eliminate potential hazards and bottlenecks in production

AI-powered process monitoring tools (e.g., Sight Machine, Rockwell FactoryTalk) can identify bottlenecks and inefficiencies in real time, augmenting the technician's oversight role.

ensures implementation of inspection, testing and evaluation methods for bought-in materials, components, semi-finished and finished products

AI-powered quality inspection systems using computer vision (e.g., Cognex, Keyence) can automate defect detection, though technicians must oversee calibration and exception handling.

plans and coordinates maintenance activities involved in manufacturing and processing procedures

AI-based predictive maintenance platforms (e.g., IBM Maximo, Azure Predictive Maintenance) can schedule maintenance based on equipment data, reducing unplanned downtime.

ensures effective completion and implementation of detailed instructions on processes, work methods and quality and safety standards for workers

AI tools like ChatGPT or Copilot can help draft and standardise work instructions and quality/safety documentation, speeding up creation while humans verify accuracy.

supports planning and production engineers in assessing existing and alternative production methods

AI tools like simulation software and digital twins can model alternative production methods, but human judgment is needed to assess practical feasibility and contextual trade-offs.

liaises with materials buying, storing and controlling departments to ensure a steady flow of supplies

AI-driven supply chain platforms (e.g., SAP IBP, Oracle AI Supply Chain) can flag supply risks and optimise ordering, but human liaison and relationship management remain essential.

supports professional engineers in reviewing safety, quality, accuracy, reliability and contractual requirements

AI can assist in reviewing compliance documentation and flagging deviations from safety and quality standards, but professional sign-off and contextual judgment remain human responsibilities.

ensures accuracy of manufacturing and testing equipment

AI can assist in analysing calibration data and flagging equipment drift, but physical verification and hands-on calibration procedures still require human technicians.

works from, and helps implement, professional engineers’ drawings and specifications for equipment and layout, and helps implement modifications required for existing plant machinery/layout

AI-assisted CAD tools (e.g., AutoCAD Copilot) can help interpret drawings, but physical implementation of equipment layout changes requires hands-on technical expertise.