In today's competitive business environment, enterprises consider supply chain management (SCM) to be a key factor for achieving cost efficiency and better profitability. A hierarchy of decisions with important economic implications has to be made in SCM – strategic, tactical, operational, and ad hoc. However, as attested by the large body of research work in this area, SCM is not a straightforward task. Supply chains (SCs) span across continents, involve numerous entities with different interests, and contend with various uncertainties. The complex maze of the network results in complex dynamics, which in turn could lead to unforeseen domino effects. These motivate the development of simulation models of the SC, which could capture the behavior of the entities, their interactions, the resulting dynamics, and the various uncertainties. These models provide decision support for SCM by allowing the user to evaluate the impact of a particular decision on the SC performance, analyze different SC policies, identify the consequences of a disruption, and determine remedial actions, through simulation.

In this paper, we present a dynamic model of a global specialty chemicals SC dealing with lubricant additive products. A typical global lubricant additive SC comprises raw material suppliers, 3rd party logistics (3PL) providers, shippers, the lubricant additive company, and customers. The lubricant additive company comprises a global sales department which directly interacts with customers and a number of lubricant additive plants in various geographical locations. In the lubricant additive SC operation, decision-making is distributed across various departments in the enterprise. Each department has its own tasks, for example the procurement department buys raw materials and the operations department makes products. Each operates based on certain rules and policies. The integrated, overall SC performance and its dynamics emerge from the combined effects of the individual actions of each department.

The entities and their interactions have been modeled as a dynamic block-based simulation model, implemented in MATLAB/Simulink. The model explicitly considers the various supply chain entities: upstream raw material suppliers, downstream customers as well as the internal entities of the lubricant additive company. These internal entities include a centralized sales department and a number of production sites located at different regions in the world. Each production site has its own procurement, scheduling, storage, operations, and packaging departments. The model simulates various supply chain activities such as raw material procurement, order assignment, job scheduling, storage, and production. Stochastic variations in transportation, production, prices, and demands are considered in the proposed model. SC infrastructure is modeled using blocks in Simulink while policies and decision-making algorithms are implemented as MATLAB m-files. This provides the user with the flexibility of simulating different policies in a plug-and-play manner. This paper describes the model and illustrates its capabilities for decision support using several case studies.