Date of Award


Publication Type


Degree Name



Industrial and Manufacturing Systems Engineering


Hoda ElMaraghy


Jacqueline Stagner



Creative Commons License

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


The traditional hot plate welding (HPW) method employing conduction heat transfer consists of four stages. Matching is the initial stage which requires an increased force applied by the heated hot plate to match the part surface to the hot plate geometry. This process eliminates normally found surface deformations and allows the hot plate to create a uniform surface ready for the Heating stage. During the Heating stage, pressure from the hot plate is removed, and the process allows the transfer of heat to the plastic part without any noticeable material displacement. Once the object is heated enough, the process is stopped, and the Change-over stage can occur. This phase refers to the time duration needed for the physical movement of the parts from their respective hot plates to the time the two components are brought in contact. Finally, the Fusion stage concludes the process by pressing the components together under pressure, allowing them to cool and solidify, thus achieving a weld. The duration of the Matching stage depends significantly on the part surface quality, size, temperature, and force exerted by the hot plate. A standard set of parameters (force, temperature, and time) and visual inspection are used during the equipment setup to examine this stage. The hot plate is applied to the part and removed throughout the trial-and-error process, where the weld surface is visually inspected for material displacement and conformance to the hot plate. In typical production settings, the time parameter for this stage is commonly set for the worst-case condition, leading to unnecessary process time for all parts, irrespective of weld pad geometry quality. The idea emerged that by quantifying nonconformance in terms of the volume of material to be displaced and incorporating the known melt displacement rate, it becomes feasible to integrate these factors into an intelligent manufacturing system. The first part of this research introduces an innovative approach for measuring the flatness of a weld pad surface in blow-moulded fuel tank manufacturing, focusing on calculating the volume of material to be displaced during the Matching stage. This chapter introduces a 3D vision system, which calculates the flatness value of the weld pad surface and converts it into the area under the curve (AUC). The AUC is then used to determine the volume of material requiring displacement, resulting in the possibility of process time adjustment for different scenarios. The second part of this research investigates the thermal expansion of high-density polyethylene (HDPE). Thermal expansion in polymers varies depending on factors such as polymer type, cross-linking, and temperature range. This variability can influence the welding process, potentially leading to extended cycle times if the equipment is not sized appropriately. The research employs a range of HDPE samples and explores different process parameters to collect data concerning sample length changes during the Matching process. An empirical model based on experimental data is formulated, providing a tool to counteract this behaviour. The third segment of this dissertation studies the material displacement of HDPE during the Matching stage. New mathematical models are introduced to simulate the relationship between key process parameters (force, temperature, time) and surface area size. The collected data was used to develop four mathematical models for material displacement and time. The results indicate that these models can be used to develop a parameter adjustment process or determine specifications for new production equipment. By successfully measuring the extent of weld pad surface nonconformance, comprehending the influential factors governing thermal expansion, and gaining insight into the material displacement rate linked to particular process parameters, it becomes feasible to develop an intelligent manufacturing system. The proposed system can be used to eliminate human decision-making and instead leverage the collected data to carry out operations more efficiently. The discoveries and knowledge gained from this study offer valuable advice for manufacturers and professionals aiming to enhance their hot plate welding processes and optimize overall operational efficiency.

Available for download on Saturday, November 16, 2024