Date of Award


Publication Type


Degree Name



Industrial and Manufacturing Systems Engineering


Optimizing systems;Sensitivity analysis;Simulation of human-robot collaboration;Simulation of manual labour;Simulation of robotics automation;White button mushroom harvesting


Jill Urbanic



Creative Commons License

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


Canada is a leading global mushroom producer, with the white button mushroom (Agaricus bisporus) being the most popular type produced. Harvesting activities are labour-intensive, and farms are currently experiencing labour shortages, which are impacting productivity, growth, and overall revenue. Robotic technologies are valid mechanisms for mushroom harvesting and demonstrate a potential to reduce this gap. Examining the performance of a harvesting system with different robotics scenarios, such as manual, robotics automation, and human robot collaboration (HRC) is crucial to realizing this potential. Simulation models are useful tools for testing and assessing systems without making any physical change to the system. In agriculture, simulation models of harvesting activities are scarce and most consider only manual operations of crops grown in greenhouses or fields. This research focuses on the development of a discrete-event simulation model in AnyLogic for different workforce scenarios (fully manual, fully automated, and HRC) in white button mushroom harvesting at the systems level to investigate the benefits and economic feasibility of each. Data for the model inputs were collected from a commercial mushroom farm and available robotic equipment. A preliminary cost analysis was performed to compare the payback periods for each scenario simulated. Results demonstrated a significantly larger overall equipment effectiveness (OEE) for automation systems, but lower production rates. The most optimal scenario for the existing commercial farm was determined to be a collaboration between automation and manual labour that featured a hybrid schedule. The agri-automation domain is a rapidly growing field, and this research will help to facilitate growth in the Canadian mushroom sector and serve as a framework and a roadmap for future harvesting simulations.