This project will help optimize COVID19 test kit distribution and allocation planning, to produce optimal outcomes for rapid testing of the population. We will conduct supply base research as input into a 50-state distribution model to inform decision-makers in how to connect suppliers of materials to testing centers, and develop a second model for testing of patients who may have contracted the virus. This model would be used to inform test manufacturers, distributors, public health officials, hospitals and commercial laboratories with testing capabilities, as well as state and federal government decision-makers.

Additive manufacturing (AM) offers a potentially game changing approach for manufacturing products. Together, industry and academia are working towards identifying the opportunities and tackling the associated challenges of employing AM technology for final-use part production. Notable AM operational challenges include: (i) integrating the technology into the industry; (ii) optimizing the productivity within the build chamber; and (iii) utilizing resources more effectively (e.g. existing manufacturing capacity, additive manufacturing capacity, labor). The research proposed aims to contribute clarity towards the third operational challenge listed, utilizing the collection of resources most effectively within a production environment consisting of both AM and traditional manufacturing (TM) technologies. The primary aim of the research focuses on scheduling and dispatch policies for an AM-TM resourced facility through cost modelling analysis. A secondary aim of research investigates the associated inventory policies for all types of the associated system entity flow (i.e. raw materials, work-in-progress, and finished goods).

Globalization in the manufacture of furniture has resulted in severe erosion in the number and scale of domestic furniture producers. Casegoods manufacturers have been the most severely impacted, although import competition in upholstered goods continues to accelerate. Possible explanations for the development of this situation abound. These include the high cost of labor and regulation in the U.S., government subsidies of foreign producers, failure to invest in manufacturing and information technology, poor asset utilization (single shift operation), failure to advertise and ?connect? with consumers, stagnant product innovation, and a retailing system that emphasizes price and destroys margins, as well as many others. The rapid movement of furniture production to off-shore sources has significantly increased the need for efficient, reliable supply chains. In addition, because of the relatively longer supply leadtimes and the resulting increase in uncertainty, inventory control policies have become more critical for balancing customer service levels and inventory costs. These issues face a number of manufacturing industries. In this proposal we address three aspects relating to supply chain sourcing and inventory analysis: (1) Mitigation of supply uncertainty; (2) Modeling unsatisfied demand and assessing realistic lost sales penalty costs; and (3) Analysis of robust supply strategies in the face of uncertainty.

NCSU will review the academic literature on the topic of staffing for service job shops, especially as it relates to staffing decisions that provide effective support for job scheduling procedures. Specifically, NCSU will review deterministic, constrained optimization techniques; stochastic modeling techniques; and empirically-driven, simulation-based approaches. NCSU will use the knowledge gained from the literature search---supplemented with a generalized understanding of service job shop processes of interest provided by Xerox---to recommend models found in the literature for building staffing plans that connect to Xerox processes and effectively complement the job scheduling process. NCSU will recommend an analytical model or computational model, as appropriate, in each of the above three categories (deterministic optimization, stochastic modeling, simulation modeling). The findings will be documented in a research report that is suitable for public dissemination (i.e., containing no proprietary information from Xerox). This research report will be the only University Project Deliverable to be provided to Xerox as a result of this activity.