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This paper aims to identify key factors that impact operating room (OR) utilization and evaluate different scenarios on OR performance.

Five months of data were collected. stepwise regression and best subset models were used to select factors and generate regression model for OR utilization. We further used simulation to test the influence of case duration mean, case duration variation, scheduled utilization and first-case delay on OR utilization, OR cost inefficiency and patient wait time on the day of surgery.

The scheduled utilization, case cancellation and add-on cases were the most important factors identified in all models. The larger the case duration variation, the lower the OR cost efficiency and utilization, the longer the patient wait time. First-case delay and turnover times are not critical in OR utilization or cost efficiency.

OR management should focus on creating an effective way to manage case cancellation and add-on policy to tackle the change on the day of surgery. In addition, several weeks before the surgery, the management needs to consider how to schedule cases to fit the allocated OR time.

In complementary of current OR management, this research assists OR management by identifying the factors that would result in the most significant improvement on OR utilization.

High lateness and no-show percentages pose great challenges on the patient scheduling process. Usually this is addressed by optimizing the time between patients in the scheduling process and the percent of extra patients scheduled to account for absent patients. However, since the patient no-show and lateness is highly stochastic we might end up with many patients showing up on time which leads to crowded clinics and high waiting times. The clinic might end up as well with low utilization of the doctor time. The purpose of this paper is to study the effect of scheduled overload percentages and the patient interval on the waiting time, overtime, and the utilization.

Actual data collection and statistical modeling are used to model the distribution for common dentist procedures. Simulation and validation are used to model the treatment process. Then algorithm development is used to model and generate the patient arrival process. The simulation is run for various values of basic interval scheduled time between arrivals for the patients. Further, 3D graphical illustration for the objectives is prepared for the analysis.

This work initially reports on the statistical distribution for the common procedures in dentist clinics. This can be used for developing a scheduling system and for validating the scheduling algorithms developed. This work also suggest a model for generating patient arrivals in simulation. It was found that the overtime increases excessively when coupling both high basic interval and high overloading percentage. It was also found that: to obtain low overtime we must reduce the basic interval. Waiting time increases when reducing the basic scheduled appointment interval and increase the scheduled overload percentage. Also doctors’ utilization is increased when the basic interval is reduced.

This work was done at a local clinic and this might limit the value of the modeled procedure times.

This work presents a statistical model for the various procedures and a detailed technique to model the operations of the clinics and the patient arrival time which might assist researches and developers in developing their own model. This work presents a procedure for troubleshooting scheduling problems in outpatient clinics. For example, a clinic suffering from high patient waiting time is directly instructed to slightly increase their basic scheduled interval between patients or slightly reduce the overloading percentage.

This work is targeting an extremely important constituent of the health-care system which is the outpatient clinics. It is also targeting multiple objectives namely waiting times, utilization overtime, which in turn is related to the economics and doctor utilization.

This work presents a detailed modeling procedure for the outpatient clinics under high lateness and no-show and addresses the modeling procedure for the patient arrivals. This 3D graphical charting for the objectives includes a study of the multiple objectives that are of high concern to outpatient clinic scheduling interested parties in one paper.

The purpose of this study is to improve the utilization of walk-in tutors at the University of Dayton.

This paper discusses the application of mixed methods participatory action research with the use of the lean six sigma (LSS) define-measure-analyze-improve-control (DMAIC) methodology combined with discrete event simulation to improve the tutoring processes at the University of Dayton.

The impact of these improvements provided a great balance between tutor utilization and student wait time, and as a result, an increase in pay was negotiated for tutors. Additionally, two schools within the University, Engineering and Business, have seen the value of the tutoring for their students and have provided additional financial support for tutoring services. Specifically, these schools now have dedicated by-appointment tutors for their students.

Incorporating simulation within the LSS methodology provides a “prototype” simulation of the potential solutions prior to changing the process in the real world. This approach can minimize the risk of implementing solutions that are costly or ineffective. The improvement of increased tutor pay helped to demonstrate the university’s commitment to tutors and tutoring. Through continuous improvement efforts, the tutoring department has tripled the number of courses that they support through these enhanced relationships, improved utilization and the overall culture and work environment. The LSS methodology and tools combined with discrete event simulation can be used as a guide for improving other repetitive processes within the university.

This paper reviews the literature relating to concepts and definitions of productivity, utilization, and efficiency. From an analysis of these concepts and definitions, the author derives two unifying formulae, the first relating these factors to one another and the second adding in a quality factor. System improvement strategies are then discussed based on these two equations.

This paper presents an investigation on the line balancing of an automated cylinder block production transfer line in order to reduce the total cycle time and increase machine utilization in an automotive plant. Results were verified by computer simulation, which showed increased throughput and higher machine utilization as a result of line balancing.

Three main operation lines of the transfer line were identified as critical and having the highest cycle time and were chosen for optimisation study. Strategies of re‐sequencing of existing operations and tools were used to reduce the cycle time of these critical operations and to balance the line. Results of a simulation study using Simul8 software are also presented to demonstrate the increase in machine utilisation and throughput as a result of line balancing.

Owing to line balancing, the cycle time of cylinder block line was reduced from 293.9 to 200 s, an almost 32 per cent reduction. This also resulted in increased throughput and machine utilisation. Throughput was increased by 65 per cent. Machine utilization was found to increase at all stations, with the highest increase at one station was recorded from 48 to 95 per cent due to balancing.

Introduces a new application to line balancing of automotive cylinder block production line. Demonstrates that effective strategies of re‐sequencing and changing of tools can lead to more balanced production line with increased throughput and higher machining utilisation, resulting in higher productivity.

Examines how marketing research affects cycle time (the time from product conceptualization to product introduction), in technology‐driven industries. The key research question to be examined in this study is: how do the collection, dissemination and utilization of marketing research information affect cycle time? Focuses on the telecommunications industry as an industry in which technology often drives the dynamics in the marketplace. Presents an empirical examination of the key research question in an exploratory study of hardware firms in the telecommunications industry. The results suggest that the collection of marketing research does not impact cycle time significantly. However, increased frequency of dissemination of the information collected via marketing research can increase cycle time. Finds also that, while the utilization ofmarketing research in designing products can increase cycle time, utilization of marketing research for strategy development can actually reduce cycle time. Thus, incorporation of marketing research in new product development can aid the introduction of new products in a timely manner.

In the complex environment of manufacturing system, it is proper to design a production system which meets the market requirements in the most economical and competitive manner. Flexible manufacturing system (FMS) is one of the options to meet the uncertainty in demand and high variety of products. This paper aims to review the definition, classification, and measurement of manufacturing flexibility concerned with manufacturing flexibility management.

The selection process consists of the synthesis and critical evaluation of the concepts put forward in the extant literature. As a consequence of this process, three primary flexibility dimensions are identified: volume, variety and machine. Simulation approach is used to study the behavior of FMS under different demand scenarios and levels of flexibility.

Four hypotheses are tested in five different flexibility levels. The following conclusions are obtained from the study. For any flexibility level, as the traffic density (TD) increases, the system utilization increases; as the TD increases, the throughput time increases; and as the number of part type increase, the system utilization decreases. A comparison between five flexibility levels showed that flexibility level 4 is best in terms of system utilization and throughput time. Flexibility level 2 perform second best, better than flexibility level 3 and flexibility level 5 which is not in line with initial assumption. Lastly, from the above results it is concluded that partial flexibility is better as compare to no flexibility and total flexibility.

It is felt that the contribution of the paper lies in demonstrating the usefulness of simulation technique in quantifying the aspects related to FMS. The effect that a specific design variable has on a specific system level flexibility type can change with the level of part processing flexibility present and flexibility trade‐off in manufacturing systems is not inevitable. This would help the planners of FMS to think and design FMS in a holistic manner.

There are evident similarities in the way large‐scale grocery retailing has developed in Britain and France, and in the manpower planning problems confronting managers in the two countries. In France, however, significantly lower levels of part‐time work appear to be employed in this sector. This article investigates how different approaches to manpower utilisation in the two countries may relate to the way in which part‐time work has developed nationally. Specifically, it presents background data relating to the growth and utilisation of part‐time work both nationally and within food retailing. It then outlines some of the main results emerging from the author's PhD research into working patterns in this sphere. The article is edited from a paper recently presented to NEDO's Part‐time Employment Group.

The purpose of this paper is to present the simulation model for manpower planning in electrical maintenance service facility and evaluates different scenarios to improve resource utilization while meeting the desired service level.

The process systematically maps entire system of electrical fault rectification, identifies probability distributions of demand of electrical maintenance requests and its process times using historical data. The simulation software Arena was used to model the entire system and various possible improvements were evaluated to assess performance of maintenance service facility.

The simulation results obtained for the proposed changes in the system indicated the potential improvement in resource utilization while meeting the average waiting time expectations of customers.

The proposed simulation model can help maintenance people to decide the optimum number of resources to meet the agreed performance level that is expected by various stakeholders.

The paper considers the computer simulation in modeling complex real-life system for understanding the resource requirement of electrical fault maintenance facility to improve resource utilization while meeting the desired service level.