An integrated framework to handle design, complexity, and controls challenges in industrial systems

  • Author / Creator
    Haq, Jawad Ul
  • During the past few decades, there has been a significant increase in automation. Mechanical processes and operations are continuously being automated. Mechanical assemblies are no longer only mechanical, but also contain a large portion of electrical wires, connections, and controls signals. Therefore, while designing, modern mechatronics or an industrial system, the importance of electrical and control attributes cannot be ignored. Designing an industrial automation system requires the system designers to deal with a number of design, complexity, and controls challenges to ensure an efficient, productive and cost-effective system. These challenges include space (for better utilization of the available parts), electrical connections and wire harnesses (for better cable management), time (to assemble the parts along with their associated accessories), and cost. Furthermore, complexity is also an important challenge but often ignored when it comes to difficulties faced in manufacturing. Estimation of these challenges at an early design stage is difficult due to the limited availability of data but having an early estimate is helpful for system designers to make early design changes. However, limited information is available on the methods to reduce the number of parts in a control system, which is responsible for most of the aforementioned design challenges. The key to a good mechatronics system is the optimized combination of both mechanical and electrical. Therefore, while designing a mechatronics or an industrial system, controls complexity is equally important to consider along with mechanical. However, research available focuses only on the mechanical layer of the system leaving behind the electrical and controls side. This thesis provides an integrated framework to assist the system designers in early design stages; to reduce the number of electrical control parts, assembly time, and ultimately the cost. It further provides a metric to quantify controls complexity. The framework is composed of (1) an iterative design for electrical controls (DEC) methodology to reduce the number of electrical controls parts and for generating alternative electrical controls concepts, (2) a multi-attribute cost function for evaluating the cost of the concept. (3) A model to evaluate the controls complexity where controls complexity is defined as the degree to which individual wires/cables are prepared, assembled, installed, attached and the diversity in associated controls signals. (4) A control system strategy to reduce the complexity by incorporating the principles of Axiomatic Design. To demonstrate the application of the proposed framework a number of different industrial systems based on PLCs, sensors, motors, and industrial communication protocols are used. The application results show the productivity of the proposed framework for the system designers in handling design, complexity, and controls challenges.

  • Subjects / Keywords
  • Graduation date
    Spring 2019
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
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