Computer Automation in Science and Engineering for Industrial Applications

Computer automation is revolutionizing industrial applications by streamlining complex workflows and operations through intelligent control systems that maximize productivity while minimizing resource usage and enhancing safety through automated monitoring and intervention systems. This research addresses the critical need for advanced automation capabilities by developing a comprehensive framework that integrates programmable logic controllers (PLCs), distributed control systems (DCS), and supervisory control and data acquisition (SCADA) systems with artificial intelligence and machine learning algorithms for predictive maintenance and process optimization. The core innovation lies in the intelligent control architecture that combines real-time control systems for time-critical applications, computer-aided engineering (CAE) for simulation and analysis, and statistical process control with Six Sigma methodology for quality improvement and waste reduction. Key technical challenges overcome include development of seamless integration with manufacturing execution systems (MES) and enterprise resource planning (ERP) systems, implementation of robust cybersecurity and data protection measures for industrial networks, and creation of comprehensive safety instrumented systems (SIS) with functional safety validation and compliance with safety integrity levels (SIL).

The developed computer automation framework finds extensive applications across automotive manufacturing for engine assembly and just-in-time production coordination, electronics manufacturing for semiconductor fabrication and PCB assembly automation, and process industries including chemical processing and pharmaceutical manufacturing with stringent validation requirements. Practical benefits include significant improvements in overall equipment effectiveness (OEE) and production throughput, enhanced quality metrics through automated inspection and statistical control, and substantial cost reductions through predictive maintenance and energy optimization. The broader research impact encompasses advancement of Industry 4.0 integration through IoT connectivity and digital twin technology, establishment of international automation standards including IEC and ISO compliance frameworks, and development of comprehensive educational programs including automation engineering curriculum and professional certification. The team’s expertise in intelligent control systems, industrial process integration, and safety engineering positions them to collaborate with automotive manufacturers, electronics companies, and process industry leaders seeking to enhance their automation capabilities through computer-integrated systems and pursue emerging opportunities in 5G connectivity for ultra-low latency communication, edge computing for distributed intelligence, and quantum computing for complex optimization and control algorithms.

For complete technical details and experimental results, please refer to the original publication: case-vazquez-santiago-2021.pdf