Title

Sustainable Industrial Growth Using Intelligent Models to Manage Complexity in Large Manufacturing Facilities

Submitter and Co-author information

Abdelrahman Amer, University of WindsorFollow

Standing

Graduate (Masters)

Type of Proposal

Visual Presentation

Challenges Theme

Fostering Sustainable Industry

Your Location

Windsor, Ontario, Canada

Faculty

Faculty of Engineering

Faculty Sponsor

Independent

Abstract/Description of Original Work

As industrial facilities expand, processes sometimes grow out of control. They develop into a multitude of interconnected elements and relationships, some obvious while others remain completely hidden. Moreover, the sheer size of the operations become extremely hard to comprehend, let alone, allow room for intelligent decisions.

For example, an aerospace manufacturer builds a product that requires more than 100 sub-components sourced from 30 suppliers located across North America. The manufacturer is responsible for managing and funding all shipping routes. The suppliers load their sub-components into special boxes for shipping and expect those boxes to be returned promptly in order for them to load the next batch. The manufacturer must integrate their return with their ordering using the same shipping resources, i.e. trucks. Moreover, the manufacturer has a limited storage space on site. Any more storage must be kept in external costly storage facilities. The mismanagement of shipping routes, shipping schedules, inventory space and even truck packing methods will lead to the waste of thousands of dollars or late deliveries, or both, on a weekly basis.

Process experts such as industrial engineers need to be hired to help manage this monstrosity developing a tailored solution relevant to the client’s needs, allowing them to continue to grow sustainably. These solutions come in the form of mathematical models, that represent real-life problems, that can be solved using intelligent search algorithms. This, coupled with a user interface, ultimately provides a decision support system that aids managers with their enormous responsibility.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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Sustainable Industrial Growth Using Intelligent Models to Manage Complexity in Large Manufacturing Facilities

As industrial facilities expand, processes sometimes grow out of control. They develop into a multitude of interconnected elements and relationships, some obvious while others remain completely hidden. Moreover, the sheer size of the operations become extremely hard to comprehend, let alone, allow room for intelligent decisions.

For example, an aerospace manufacturer builds a product that requires more than 100 sub-components sourced from 30 suppliers located across North America. The manufacturer is responsible for managing and funding all shipping routes. The suppliers load their sub-components into special boxes for shipping and expect those boxes to be returned promptly in order for them to load the next batch. The manufacturer must integrate their return with their ordering using the same shipping resources, i.e. trucks. Moreover, the manufacturer has a limited storage space on site. Any more storage must be kept in external costly storage facilities. The mismanagement of shipping routes, shipping schedules, inventory space and even truck packing methods will lead to the waste of thousands of dollars or late deliveries, or both, on a weekly basis.

Process experts such as industrial engineers need to be hired to help manage this monstrosity developing a tailored solution relevant to the client’s needs, allowing them to continue to grow sustainably. These solutions come in the form of mathematical models, that represent real-life problems, that can be solved using intelligent search algorithms. This, coupled with a user interface, ultimately provides a decision support system that aids managers with their enormous responsibility.