Date of Award

2023

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

First Advisor

W. ElMaraghy

Second Advisor

H. ElMaraghy

Third Advisor

E.Kim

Keywords

Digital twins, Greenhouse management, Maturity assessment model, Value stream mapping

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

With the rise in the global population, Greenhouse farming (GF) can help the agriculture sector by enabling year-round plant production regardless of location, climate, and other environmental factors. However, this will be realized when they can properly manage their production processes and limited resources. The lack of accurate and sufficient data is a significant barrier to traditional GF, and growers make daily decisions based on expenses rather than actual needs. A Digital Twin at their value stream level (DT-VS) is an emerging technology that can benefit this industry by giving decision-makers more precise insight into their business. However, to employ such technology in Greenhouses, understanding where they stand is a prerequisite for deciding future actions.

This thesis presents a method called "A Maturity Assessment Model for Digital Twin-Value Stream Technology in Greenhouses" to help greenhouse farmers manage their production processes and limited resources more effectively using digital twin technology. The model includes a questionnaire, numerical equations, and an assessment procedure to guide farmers in finding gaps and developing a strategic roadmap to transition from traditional greenhouse management to real-time monitoring and intelligent decision-making.

The proposed model has been validated through multiple use cases and case studies, with greenhouse participants reporting that implementing more cutting-edge technology can significantly accelerate their progress toward their business goals. According to the data analysis, 60% think that their current technology ecosystem helps them achieve their business goals, and 70% believe that implementing more cutting-edge technology than they currently use can greatly accelerate their progress toward those goals.

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