Timothy Sprock

Simulation model generation of discrete event logistics systems (dels) using software design patterns

To provide automated access from a formal system model to multiple analysis tools, such as discrete event simulation or optimization, we extend current model-based systems engineering (MBSE) methodologies by introducing a new model to model transformation method based on object-oriented creational patterns from software design. Implemented in MATLABs discrete event simulation tool, SimEvents, we demonstrate the methodology by generating two distinct use cases based on a distribution supply chain and manufacturing system.

Automated production system simulations using commercial off-the-shelf simulation tools

A multi-year research project focused on a global aerospace companys design-to-production transition, and in particular how to answer production-related questions much earlier in a programs design cycle than is possible today. A fundamental difficulty is that the time and expertise required to formulate appropriate analysis models prevents their routine use, especially in new program development. The projects goal was to reduce these requirements, and by late 2014 a methodology had been developed for on-demand analysis generation to answer routine questions about production systems. A pilot project was conducted in 2015 to demonstrate efficacy, that an implementation of the methodology could in fact reduce by at least an order of magnitude the time required to answer a frequently-asked question, in a repeatable way while specification of the products, their process plans, planned facilities, and available resources were frequently changing. This paper summarizes the methodology, its pilot project implementation, and preliminary results.

A hierarchical approach to warehouse design

Abstract The design of large complex systems, such as warehouses, requires multiple experts and analyses as well as methods to organise and integrate their knowledge. While there are many models for optimising individual aspects of warehouses, there is not, today, a comprehensive design methodology that incorporates and supports all of the design decisions and provides a method to effectively integrate the solutions to these subproblems into a complete warehouse system specification. In this research, we propose a hierarchical design decision support methodology based on decomposing the design problem into a set of subproblems and using a formal model of the system to integrate the solutions to these subproblems. The methodology enables a thorough search of the design space and the identification of many candidate designs for consideration by the design decision maker. The hierarchical design methodology is demonstrated with an example of designing a forward pick area.

A simulation optimization framework for discrete event logistics systems (DELS)

For large-scale, complex systems, both simulation and optimization methods are needed to support system design and operational decision making. Integrating the two methodologies, however, presents a number of conceptual and technical problems. This paper argues that the required integration can be successfully achieved, within a specific domain, by using a formal domain specific language for specifying instance problems and for structuring the analysis models and their interfaces. The domain must include a large enough class of problems to justify the resulting specialization of analysis models.

Simulation optimization in discrete event logistics systems: the challenge of operational control

Simulation optimization tools have the potential to provide an unprecedented level of support for the design and execution of operational control in Discrete Event Logistics Systems (DELS). While much of the simulation optimization literature has focused on developing and exploiting integration and syntactical interoperability between simulation and optimization tools, maximizing the effectiveness of these tools to support the design and execution of control behavior requires an even greater degree of interoperability than the current state of the art. In this paper, we propose a modeling methodology for operational control decision-making that can improve the interoperability between these two analysis methods and their associated tools in the context of DELS control. This methodology establishes a standard definition of operational control for both simulation and optimization methods and defines a mapping between decision variables (optimization) and execution mechanisms (simulation / base system). The goal is a standard for creating conforming simulation and optimization tools that are capable of meeting the functional needs of operational control decision making in DELS.