Author ORCID Identifier
0000-0002-8879-1016
Document Type
Thesis
Date of Award
Spring 5-5-2026
Keywords
Application Programming Interface, Workflow automation, Manufacturing environments, Manufacturing Execution Systems, Optimization, SCADA
Degree Name
Master of Science in Industrial Engineering (MSIE)
Department
Systems Science and Industrial Engineering
First Advisor
Daryl Santos
Abstract
This research addresses inefficiencies in Manufacturing Execution System (MES)-driven workflows, where excessive user interactions and fragmented access to work instructions introduce transactional and cognitive waste. To address these limitations, an integrated architecture was developed using Ignition as a SCADA-based operator interface connected to the MES through API-based communication. The system replaces direct MES interaction with a unified interface that embeds work instructions and automates transaction execution within the production workflow. The approach was implemented and evaluated through an industrial case study on a 15 station electronics manufacturing line. Results show a 51% reduction in total cycle time, decreasing from 2,996 seconds to 1,454 seconds. Process performance improved substantially, with rolled throughput yield increasing from 17.77% to 62.87%, alongside improved first-pass yield across stations. The redesign also resulted in an estimated $290,000 in annual cost savings and a 45% increase in operator satisfaction. These findings demonstrate that a significant portion of manufacturing inefficiency originates from the design of the operator interaction layer rather than the physical process itself. By decoupling interface execution from backend transaction systems and aligning digital workflows with physical task sequences, the study highlights the importance of operator-centric design in improving performance in digital manufacturing environments.
Recommended Citation
Alalul, Kamal, "Digital Lean Transformation Through MES–SCADA Intergration: Reducing Transactional and Cognitive Waste in High-Volume Electronics Manufacturing" (2026). Graduate Dissertations and Theses. 441.
https://orb.binghamton.edu/dissertation_and_theses/441
Included in
Industrial Engineering Commons, Industrial Technology Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Engineering Commons, Systems Science Commons