Temporal manufacturing query language (tMQL) for domain specific composition, what-if analysis, and optimization of manufacturing processes with inventories

Download paper here

Smart manufacturing requires streamlining operations and optimizing processes at a global and local level. This paper considers manufacturing processes that involve physical or virtual inventories of products, parts and materials, that move from machine to machine. The inventory levels vary with time and are a function of the configuration settings of the machines involved in the process. These environments require analysis, e.g., answering what-if questions, and optimization to deter- mine optimal operating settings for the entire process. The modeling complexities in performing these tasks are not always within the grasp of production engineers. To address this problem, the paper proposes the tempo- ral Manufacturing Query Language (tMQL) that allows the composition of modular process models for what-if analysis and decision optimization queries. tQML sup- ports an extensible and reusable model knowledge base against which declarative queries can be posed. Addi- tionally, the paper describes the steps to translate the components of a tMQL model to input data files used by a commercial optimization solver.

Recommended citation: M. Krishnamoorthy, A. Brodsky, and D. A. Menasce, Temporal manufacturing query language (tMQL) for domain specific composition, what-if analysis, and optimization of manufacturing processes with inventories. Technical Report Department of Computer Science, George Mason University, 2014. Also presented at the 2015 INFORMS Computing Soc. Conf. workshop, Richmond, VA. January 2015.