Vijith Varghese

An object-oriented framework for simulating multi-echelon inventory systems

In this paper, we discuss the design and use of an object-oriented framework for simulating multi-echelon inventory systems. We present a context for how the framework can be used through its application on two examples. In addition, we describe the design by examining the major conceptual artifacts within the object-oriented model. The framework is built on a Java Simulation Library (JSL) and permits easy modeling and execution of simulation models. The results and discussion indicate the flexibility and power of modeling with the framework. In addition, we summarize our future research efforts to model complex supply chains

Simulating inventory systems with forecast based policy updating

This paper presents an object oriented framework that facilitates modeling inventory systems whose policy updating is driven by forecast estimates. In an inventory system, the forecast estimates and the forecast error measures are used to set the inventory policy. A simulation approach can address questions regarding the choice of the forecasting technique and the frequency of updating the policy, especially in non-stationary demand scenarios. This paper discusses how the framework can be used to develop simulation models through which these questions can be addressed. In addition, two examples illustrate how to use the framework and how to analyze supply chains with forecast based policy updating.

A decision support tool for healthcare providers to evaluate readiness and impacts of adopting supply chain data standards

Healthcare providers are under increasing pressure to reduce waste, eliminate unnecessary costs and redundant efforts, thereby improving the quality and consistency of healthcare delivery. Lack of automation and the lack of use of global identifiers for products and locations, also known as supply chain data standards, are two critical factors that can help streamline providers operations and improve process efficiency. Despite widespread consensus among various stakeholders, healthcare providers lack a well-defined approach towards adopting and implementing data standards. Supply chain data standards can be defined as a set of product and location identifiers which are used in supply chain related processes and transactions. Healthcare providers willing to successfully adopt data standards in some or all of their operations need to invest in several process changes and technology installations or upgrades; however, they often struggle to justify returns on those investments and hence, find uncertain Return on Investment (ROI) as a critical barrier. In this article, we present a hierarchical comprehensive spreadsheet based decision support tool that helps potential healthcare providers to evaluate their readiness requirements and quantify the potential impacts of their decisions in terms of non-monetary performance measures, such as increased productivity, enhanced patient safety and reduction in errors resulting in decreased volume of transactions. This tool has undergone extensive testing with healthcare providers of different size, scope, and needs. We present numerical results showcased through practical examples in this article. The software is publicly available free of cost for download at http://cihl.uark.edu.

Investigating the effect of demand aggregation on the performance of an (R, Q) inventory control policy

This paper investigates the effect of demand aggregation on the performance measures of an inventory system controlled by a (r, Q) policy. Demand usage data is available at different time scales, i.e., daily, weekly, monthly etc., and forecasting is based on these time scales. Using forecasts, appropriate lead time demand models are constructed and used in optimization procedures. The question being investigated is what effect the forecasting time bucket has on whether or not the inventory control model meets planned performance. A simulation model is used to compare performance under different demand aggregation levels. The simulation model of the optimized (r, Q) inventory system is run for the planning horizon and the supply chain operational performance measures like ready rate, expected back order etc., are collected. Subsequently, the effect of aggregating the demand and planning accordingly is analyzed based on the simulated supply chains operational performance.

An Exploratory Pilot Study on Supply Chain Data Standards in a Hospital Pharmacy

Abstract Supply chain data standards provide unique and unambiguous references to products and locations, enable system level interoperability, facilitate barcode-based medication administration, and offer track-and-trace capabilities throughout the healthcare supply chain. Despite widespread consensus among industry stakeholders and many perceived benefits, healthcare providers are hesitant to implement these standards. Through an exploratory pilot study at a healthcare provider site focused on pharmaceutical operations, we identify the key challenges in implementing data standards in a pharmaceutical setting. In doing so, we document the required technology functionality, clinical and financial workflows, and information systems, as well as articulate the challenges in implementing data standards. The lessons learned from the study offer valuable insights for supply chain executives, engineering managers, and pharmacy directors to plan and implement GS1 standards in their facilities.