The Faculty Notebook, December 2006

The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost

Towards Leaner Healthcare Facility: Application of Simulation Modelling and Value Stream Mapping

Recently, the application of lean thinking in healthcare has grown significantly in response to rising demand caused by population growth, ageing and high expectations of service quality. However, insufficient justifications and lack of quantifiable evidence are the main obstacles to convince healthcare executives to adopt lean. Therefore, this paper presents a methodology that integrates lean tools with simulation to enhance the quality of patient care in healthcare facilities. This enables healthcare organisations to dedicate more time and effort to patient care without extra cost to the organisation or to the patient. Value stream mapping is used to identify value-added and non-value-added activities.. Then, a comprehensive simulation model is developed to account for the variability and complexity of healthcare processes and to assess the gains of proposed improvement strategies. An extensive analysis of results is provided and presented to managers to illustrate the potential benefits of adapting lean practices

2006 Author Recognition Bibliography

https://scholarworks.gvsu.edu/authorrecognition/1008/thumbnail.jp

Materials Supply System Analysis Under Simulation Scenarios in a Lean Manufacturing Environment

AbstractIdentifying the most efficient supply system for a company working under Lean Manufacturing practices was possible with the support of this work. Promodel software was used to develop simulation model depicting a constant velocity joints (CVJ) production system, where two different supply methods were assessed. According to results herein obtained, better performance is achieved under random supply method in comparison with a clustering supply method. The company’s goal is to keep 1% losses due to lack of material. In the actual process, this essential parameter was reduced from 2.73% to 1.177%, if random supply method is properly implemented

Reducing Lead Times in a two-process cell using lean and simulation.

An existing power system production process includes two operations and produces twelve different part types. The first operation fills WIP carts used by the second operation. A combined lean and discrete event simulation study supported by the analysis of order history information stored in a corporate information system is presented. The goal was to identify operations alternatives that could be used to reduce customer lead time from the current 3 to 3 days to 1 to 3 days. The application of lean methods included the examination of the order history data that showed that 80% of parts ship to a single primary customer and 20% to many secondary customers. The lean part of the study further concluded that the number of WIP carts should equal the number of different products, that each WIP cart should be associated with one and only one product and that each WIP cart should be should refilled daily after orders are processed. Using a discrete event simulation model, four order processing sequencing alternatives for improving on-time delivery were evaluated. The percent of orders delivered in 1 day was maximized, with the lowest variance, by sorting all orders for the primary customer first from smallest in size to largest. The orders for the same product from the remaining customers are processed immediately after the order for the same product from the primary customer. The value of the synergistic effect of combining lean tools with simulation supported by order data extracted from the corporate information system is demonstrated

Application of Lean Thinking Using Simulation Modelling in a Private Hospital

Timely access, prompt responses to patient needs, and availability of resources to deliver quality service are the key priorities of healthcare systems, in particular hospitals. To cope with these constraints, healthcare managers have turned into lean thinking and approaches in their attempts to reduce non-value added activities and save costs by reducing wastes. This paper presents a case study of a private hospital in Dublin that used integrated approach of value stream mapping and simulation modeling to assess lean implementation in admission and discharge processes. Simulation enabled the strategic management to examine the outcomes of three possible improvement scenarios on hospital performance before implementing lean strategies. The proposed methodology helped to identify bottlenecks and non-value added procedures. Results analysis showed potential improvement in patients’ admission and discharge cycle times and offered the hospital the cost-saving opportunity of reducing the numbers of bed required

A simulation-enhanced lean design process

A traditional lean transformation process does not validate the future state before implementation, relying instead on a series of iterations to modify the system until performance is satisfactory. An enhanced lean process that includes future state validation before implementation is presented. Simulation modeling and experimentation is proposed as the primary validation tool. Simulation modeling and experimentation extends value stream mapping to include time, the behavior of individual entities, structural variability, random variability, and component interaction effects. Experiments to analyze the model and draw conclusions about whether the lean transformation effectively addresses the current state gap can be conducted. Industrial applications of the enhanced lean process show it effectivenessPeer Reviewe

Proposition of a method for stochastic analysis of value streams

This article aims at proposing a method to stochastically analyze values streams taking into consideration the effect of critical uncertainty sources on lead time. The proposed method combines value stream mapping (VSM) and Monte Carlo simulation to identify improvement opportunities. To illustrate this approach, we carried out a case study in the special nutrition value stream of a Brazilian public hospital. Results show that the proposed method allows the identification of improvement opportunities that would not be considered in the classical deterministic VSM approach. Further, the integration of the stochastic analysis enables the determination of a more realistic lead time, which supports a more assertive planning and scheduling of the value stream. The proposed method addresses a fundamental gap in traditional VSM without adding much complexity to the analysis procedure, which is a common practical issue in previous works that integrated other stochastic methods into VSM

LCA to support decision-making in layout designs

Introduction The economic impact of environmental regulations in the manufacturing sector and the increasing costs of primary resources have pressured companies wishing to obtain competitive advantages to seek ways to rationalize these resources, either through changes in products specifications or in manufacturing process. These actions depend on solutions that should consider the limits set out in the interdependencies between economic, environmental and social areas, which comprise the so-called sustainability tripod. In this case, the guiding principle for decisions should follow the approach of sustainable development. For this purpose, a proper performance indicators evaluation of processes is a great step to improvement actions and decision making for modifications. Continuous improvement approaches and support of mathematical tools, such as the Discrete Event Simulation (DES) have been used for identifying waste on the shop floor and for cost analyses for manufacturing optimization (Standridge et al. 2006). One of the advantages resulting from the application of DES in corporations is its capability to include the impact of randomness in a system. All the dynamics and the non-deterministic nature of the parameters eliminate the use of static tools such as spreadsheets for solving many line design problems. Furthermore, all commercial simulation software provides detailed animation capabilities. The animation of the manufacturing process and flow can help engineers to visually detect problems or bottlenecks and also to test out alternate line designs. For this reason, the DES may be applied to generate requirements and sustainable systems specifications for manufacturing. However, the analyses results performed by using DES are not sufficient for the joint assessment of impacts on the three dimensions of sustainability (Johansson et al. 2010; Kuhl & Zhou 2009; Joschko et al. 2009). A tool widely used in the academic environment and by corporations to calculate pollutant emissions rates in the product life cycle is Life Cycle Assessment (LCA). This can supplement cost assessments performed with DES in the production process phase. This work discusses the combined use of DES with LCA to analyze production resources utilization in manufacturing systems. Towards this end, it seeks through a case study to analyze this joint use in decision-making for purchasing forklifts, according to sustainable premises