Advancements in digitization have enabled two sided manufacturing-as-a-service (MaaS) marketplaces which has significantly reduced product development time for designers. These platforms provide designers with access to manufacturing resources through a network of suppliers and have instant order placement capabilities. Two key decision making levers are typically used to optimize the operations of these marketplaces: pricing and matching. The existing marketplaces operate in a centralized structure where they have complete control over decision making. However, a decentralized organization of the platform enables transparency of information across clients and suppliers. This dissertation focuses on developing tools for decision making enabling decentralization in MaaS marketplaces. In pricing mechanisms, a data driven method is introduced which enables small service providers to price services based on specific attributes of the services offered. A data mining method recommends a network based price to a supplier based on its attributes and the attributes of other suppliers on the platform. Three different approaches are considered for matching mechanisms. First, a reverse auction mechanism is introduced where designers bid for manufacturing services and the mechanism chooses a supplier which can match the bid requirements and stated price. The second approach uses mechanism design and mathematical programming to develop a stable matching mechanism for matching orders to suppliers based on their preferences. Empirical simulations are used to test the mechanisms in a simulated 3D printing marketplace and to evaluate the impact of stability on its performance. The third approach considers the matching problem in a dynamic and stochastic environment where demand (orders) and supply (supplier capacities) arrive over time and matching is performed online.

The interwebs, as of late, have been filled with images created by artificial intelligence rendering bots such as DALL-E and Midjourney -- and the humans (I think they're humans) using them as tools. Brooklyn-based artist Zach Katz has used it to reimagine the urban design of cities. A reporter at SFGATE has undertaken a similar project, asking DALL-E 2 to retool some of the city's architecture and infrastructure. In July, the Guardian rounded up four artists to come up with unlikely prompts -- such as "biotech harpy in field at sunset" -- for DALL-E Mini (the free, public version of DALL-E). Naturally, the advent of bots that can create an image out of a simple text command is drawing the scrutiny of illustrators.

According to the annual "Financial Ratios & Operational Benchmarking Survey" from the Fabricators & Manufacturers Association International, the average usually hovers around 30 percent, though the range varies widely depending on a fabricator's customer mix and specialty. For some the ratio is actually much lower. Of all the time and effort estimators spend answering requests for quote, only about 30 percent of their work turns into something of value--a work order. Put in manufacturing terms, the quoting process has a 70 percent "scrap" rate. Sure, a high reject rate is the nature of the quoting beast (some prospects are probably just window shopping), but it's still an extraordinarily inefficient beast.

Predicting the future is hard. It's nearly impossible to know what technological marvels await in the next few years, let alone the next eight decades. Undaunted, we've put together a list of 10 super-advanced technologies that should be around by the year 2100. Some of these technologies are rather "out there," but I'm reasonably confident in making these predictions. As radical as some of the items described here appear, most--if not all--should be around by the turn of the 22nd century.

Predicting the future is hard. It's nearly impossible to know what technological marvels await in the next few years, let alone the next eight decades. Undaunted, we've put together a list of 10 super-advanced technologies that should be around by the year 2100. Some of these technologies are rather "out there," but I'm reasonably confident in making these predictions. As radical as some of the items described here appear, most--if not all--should be around by the turn of the 22nd century.