<p>The high luminosity phase of the LHC, poised to start taking data in 2027, aims to increase the instantaneous luminosity of the machine to 7.5 x 10³⁴ cm^-2 s^-1. This will make it possible for experiments at CERN to make higher precision measurements on known physics phenomenon as well as to search for “new physics”. However, this motivates the need for hardware upgrades at the various experiments in order to ensure compatibility with the HL-LHC. This thesis describes some of the efforts to upgrade the inner-most layers of the Compact Muon Solenoid, namely the CMS silicon pixel tracking detector. </p> <p>Silicon sensors used to track particles are installed in the detector as part of a pixel sensor module. Modules consist of a silicon sensor-readout chip assembly that is wire-bonded to an HDI, or High Density Interconnects to provide power and signals. </p> <p>As part of the upgrade, 2,541 modules need to be assembled delicately and identically with alignment error margins as low as 10 microns. Assembly will be across three production sites in clean rooms to avoid dust and humidity contamination.</p> <p>In addition, the modules need to survive high magnetic fields and extended close-range radiation as part of the HL-LHC.</p> <p>In line with this effort, new materials and assembly procedures able to sustain such damage are investigated. Techniques to assemble modules are explored, specifically precision placing of parts with a robotic gantry and techniques to protect wirebonds. This is followed by a discussion of the accuracy and repeatability.</p>

The allocation of resources over time, referred to as resource scheduling, in large-scale construction environments is a challenging problem. Although traditional network scheduling techniques are the most popular scheduling techniques in the construction industry, they are ineffective in modeling the dynamic nature and resource interactions of large projects. Simulation based modeling or optimization techniques are also time-consuming, complicated and costly to be implemented in large-scale projects. This research is focused on developing a new framework to insert artificial intelligence inside construction simulations for facilitating the resource allocation process. The first stage in this study was developing a framework to solve resource scheduling problems in large scale construction projects. This framework, called the Simulation Based Auction Protocol (SBAP), integrates Multi-Agent Resource Allocation (MARA) in a simulation environment. This hybrid framework deploys centralized MARA (i.e., auction protocols) whereby agents bid on different combinations of resources at the start of a simulation cycle. Agents attempt to improve their individual welfare by acquiring a combination of resources. An auctioneer is designed to allocate resources to the agents by maximizing the overall welfare of the society. Simulation is also employed to track the availability of resources, and manage resource oriented activities. This framework is implemented in two large construction applications of scheduling module assembly yard and multiple heavy lift planning in modular construction. The second objective of this project is to develop a generic resource allocation component for addressing optimized resource allocation in various construction projects. This component is developed in a large scale model using High Level Architecture (HLA), instead of traditional simulation environments. HLA allows splitting a large scale model, known as a federation, into a number of manageable components (i.e., federates), while maintaining interoperability between them. A generic Resource Allocation (RA) federate is designed to act as an auctioneer for federates developed based on the SBAP. Another generic federate is also built to automate the communication with the RA federate. These two generic federates can be reused in various construction federations. This framework is successfully implemented in an industrial construction process that involves different supply chains including spool fabrication, module assembly and heavy crane lifts in site construction. / Construction Engineering and Management

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