scholarly journals Continuous process improvement implementation framework using multi-objective genetic algorithms and discrete event simulation

2019 ◽  
Vol 25 (5) ◽  
pp. 1020-1039 ◽  
Author(s):  
Parminder Singh Kang ◽  
Rajbir Singh Bhatti
Keyword(s):  
Discrete Event Simulation ◽  
Process Improvement ◽  
Continuous Process ◽  
Discrete Event ◽  
Buffer Size ◽  
Size Optimization ◽  
Continuous Process Improvement ◽  
Content Type ◽  
Event Simulation ◽  
Job Sequencing

Purpose Continuous process improvement is a hard problem, especially in high variety/low volume environments due to the complex interrelationships between processes. The purpose of this paper is to address the process improvement issues by simultaneously investigating the job sequencing and buffer size optimization problems. Design/methodology/approach This paper proposes a continuous process improvement implementation framework using a modified genetic algorithm (GA) and discrete event simulation to achieve multi-objective optimization. The proposed combinatorial optimization module combines the problem of job sequencing and buffer size optimization under a generic process improvement framework, where lead time and total inventory holding cost are used as two combinatorial optimization objectives. The proposed approach uses the discrete event simulation to mimic the manufacturing environment, the constraints imposed by the real environment and the different levels of variability associated with the resources. Findings Compared to existing evolutionary algorithm-based methods, the proposed framework considers the interrelationship between succeeding and preceding processes and the variability induced by both job sequence and buffer size problems on each other. A computational analysis shows significant improvement by applying the proposed framework. Originality/value Significant body of work exists in the area of continuous process improvement, discrete event simulation and GAs, a little work has been found where GAs and discrete event simulation are used together to implement continuous process improvement as an iterative approach. Also, a modified GA simultaneously addresses the job sequencing and buffer size optimization problems by considering the interrelationships and the effect of variability due to both on each other.

scholarly journals Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation

Processes ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 660
Author(s):  
Félix Badilla-Murillo ◽  
Bernal Vargas-Vargas ◽  
Oscar Víquez-Acuña ◽  
Justo García-Sanz-Calcedo
Keyword(s):  
Resource Utilization ◽  
Discrete Event Simulation ◽  
Current System ◽  
Waiting Times ◽  
Continuous Process ◽  
Discrete Event ◽  
Computer Software ◽  
Productive Capacity ◽  
Continuous Process Improvement ◽  
Event Simulation

The installed productive capacity of a healthcare center’s equipment limits the efficient use of its resources. This paper, therefore, analyzes the installed productive capacity of a hospital angiography room and how to optimize patient demand. For this purpose, a Discrete Event Simulation (DES) model based on historical variables from the current system was created using computer software. The authors analyzed 2044 procedures performed between 2014 and 2015 in a hospital in San José, Costa Rica. The model was statistically validated to determine that it does not significantly differ from the current system, considering the DMAIC stages for continuous process improvement. In the current scenario, resource utilization is 0.99, and the waiting list increases every month. The results showed that the current capacity of the service could be doubled, and that resource utilization could be reduced to 0.64 and waiting times by 94%. An increase in service efficiency could be achieved by shortening maximum waiting times from 6.75 days to 3.70 h. DES simulation, therefore, allows optimizing of the use of healthcare systems’ resources and hospital management.

Supporting process improvements with process mapping and system dynamics

2018 ◽  
Vol 67 (8) ◽  
pp. 1255-1270 ◽  
Author(s):  
David E. Bowles ◽  
Lorraine R. Gardiner
Keyword(s):  
System Dynamics ◽  
Discrete Event Simulation ◽  
Process Improvement ◽  
Simulation Modeling ◽  
Discrete Event ◽  
Process Mapping ◽  
Content Type ◽  
Process Improvements ◽  
Event Simulation

Purpose The purpose of this paper is to study the effectiveness of combining process mapping and system dynamics (SD) in an organization’s ongoing business process improvement projects. Design/methodology/approach Norfield Industries, designer and manufacturer of prehung door machinery, used process mapping and SD in a project targeting the improvement of its design document control process. The project team first used process mapping to document its current process and identify potential improvements. The team then developed an SD model to investigate the potential impacts of proposed process changes. Findings The case study supports the communication and transparency benefits of process mapping reported in earlier studies. Consistent with other case studies using simulation, SD provided useful insights into possible results of proposed process changes. Research limitations/implications The findings have limitations with respect to generalizability consistent with the use of a case study methodology. Practical implications Organizational managers desiring to include simulation modeling in process improvement efforts have a choice between discrete event simulation and SD. SD may prove able to consume less organizational resources than discrete-event simulation and provide similar benefits related to reducing the risks associated with process changes. Originality/value The current case study adds to the existing literature documenting the use of process mapping combined with simulation modeling in process improvement efforts. The case study supports existing literature regarding the value of process mapping in making system processes more transparent. The results also support previous findings regarding the value of SD for simulating the possible results associated with scenarios under consideration for process improvements.

scholarly journals Measuring lean implementation for maintenance service companies

2016 ◽  
Vol 7 (1) ◽  
pp. 35-61 ◽  
Author(s):  
Stephan J. de Jong ◽  
Wouter W.A. Beelaerts van Blokland
Keyword(s):  
Transaction Cost ◽  
Discrete Event Simulation ◽  
Continuous Improvement ◽  
Lean Manufacturing ◽  
Discrete Event ◽  
Asset Specificity ◽  
Lean Implementation ◽  
Content Type ◽  
Event Simulation ◽  
Maintenance Service

Purpose – Implementation of lean manufacturing is currently performed in the production industry; however, for the airline maintenance service industry, it is still in its infancy. Indicators such as work in process, cycle time, on-time performance and inventory are useful indicators to measure lean implementation; however, a financial economic perspective taking fixed assets into consideration is still missing. Hence, the purpose of this paper is to propose a method to measure lean implementation from a fixed asset perspective for this type of industry. With the indicators, continuous improvement scenarios can be explored by value stream discrete event simulation. Design/methodology/approach – From literature, indicators regarding asset specificity to measure lean implementation are found. These indicators are analysed by a linear least square method to know if variables are interrelated to form a preliminary model. The indicators are tested by value stream-based discrete event simulation regarding continuous improvement scenarios. Findings – With the new found lean transaction cost efficiency indicators, namely, turnover, gross margin and inventory pre-fixed asset (T/FA, GM/FA and I/FA, respectively), it is possible to measure operation performance from an asset specificity perspective under the influence of lean implementation. Secondly, the results of implementing continuous improvement scenarios are measured with the new indicators by a discrete event simulation. Research limitations/implications – This research is limited to the airline maintenance, repair and overhaul (MRO) service industry regarding component repair. Further research is necessary to test the indicators regarding other airline MRO service companies and other sectors of complex service industries like health care. Practical implications – The lean transaction cost efficiency model provides the capability for a maintenance service company to simulate the effects of process improvements on operation performance for service-based companies prior to implementation. Social/implications – Simulation of a Greenfield process can involve employees with possible changes in processes. This approach supports the adoption of anticipated changes. Originality/value – The found indicators form a preliminary model, which contributes to the usage and linkage of theories on lean manufacturing and transaction cost theory – asset specificity.

Improving outpatient phlebotomy service efficiency and patient experience using discrete-event simulation

2016 ◽  
Vol 29 (7) ◽  
pp. 733-743 ◽  
Author(s):  
Kenneth Yip ◽  
Suk-King Pang ◽  
Kui-Tim Chan ◽  
Chi-Kuen Chan ◽  
Tsz-Leung Lee
Keyword(s):  
Discrete Event Simulation ◽  
Scenario Analysis ◽  
Performance Metrics ◽  
Discrete Event ◽  
Evidence Based ◽  
Content Type ◽  
Event Simulation ◽  
Service Efficiency ◽  
Related Service ◽  
The Relationship

Purpose – The purpose of this paper is to present a simulation modeling application to reconfigure the outpatient phlebotomy service of an acute regional and teaching hospital in Hong Kong, with an aim to improve service efficiency, shorten patient queuing time and enhance workforce utilization. Design/methodology/approach – The system was modeled as an inhomogeneous Poisson process and a discrete-event simulation model was developed to simulate the current setting, and to evaluate how various performance metrics would change if switched from a decentralized to a centralized model. Variations were then made to the model to test different workforce arrangements for the centralized service, so that managers could decide on the service’s final configuration via an evidence-based and data-driven approach. Findings – This paper provides empirical insights about the relationship between staffing arrangement and system performance via a detailed scenario analysis. One particular staffing scenario was chosen by manages as it was considered to strike the best balance between performance and workforce scheduled. The resulting centralized phlebotomy service was successfully commissioned. Practical implications – This paper demonstrates how analytics could be used for operational planning at the hospital level. The authors show that a transparent and evidence-based scenario analysis, made available through analytics and simulation, greatly facilitates management and clinical stakeholders to arrive at the ideal service configuration. Originality/value – The authors provide a robust method in evaluating the relationship between workforce investment, queuing reduction and workforce utilization, which is crucial for managers when deciding the delivery model for any outpatient-related service.

Evaluation of postponement strategy in the production of table wine in Brazil: a discrete event simulation approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carolina Reis Gualberto ◽  
Lásara Fabrícia Rodrigues ◽  
Karine Araújo Ferreira
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Real Life ◽  
Minas Gerais ◽  
Future Research ◽  
Lost Sales ◽  
Wine Production ◽  
Content Type ◽  
Event Simulation ◽  
Postponement Strategy

Purpose The purpose of this paper is to develop an approach to evaluate the partial postponement strategy and compare it with postponement and make-to-stock (MTS) strategies in the production of table wine in wineries in the state of Minas Gerais (south-eastern Brazil). Design/methodology/approach An approach based on discrete event simulation was developed to support decision-making in the wine sector. Simulation models were used to analyse partial postponement, postponement and MTS strategies in wine production. These models were inspired by a typical table wine producer selected from an exploratory study conducted in 12 wineries of Minas Gerais state in Brazil. Findings Hybrid strategies, such as partial postponement, favour the advantages of postponement and MTS depending on the portion of semi-finished and finished goods adopted. Wine production characteristics favour postponement and partial postponement with high semi-finished product levels (customer order-driven product) because this allows companies to reduce their inventory of bottles, despite possible increases in lost sales and costs. MTS and partial postponement with high finished product levels (forecast-driven product) present higher costs with bottled wine storage; however, these strategies reduce lost sales and improve agility and reliability in deliveries. Research limitations/implications Future research should analyse the production of table wines in other regions of the country and the production of fine wines. Practical implications The findings suggest promising perspectives for real-life applications in wineries in Brazil and other countries. Originality/value Simulation techniques allow the analysis of production strategies in little-known industries, such as table wine production in Brazil. The approach developed is flexible enough to support decisions and to be adapted to companies’ and markets’ characteristics and to test specific strategies.

scholarly journals The application of a hybrid simulation modelling framework as a decision-making tool for TPM improvement

2019 ◽  
Vol 25 (3) ◽  
pp. 476-498 ◽  
Author(s):  
Omogbai Oleghe ◽  
Konstantinos Salonitis
Keyword(s):  
Discrete Event Simulation ◽  
Hybrid Model ◽  
Discrete Event ◽  
Simulation Modelling ◽  
Hybrid Modelling ◽  
Content Type ◽  
Event Simulation ◽  
Modelling Framework ◽  
Field Notes

Purpose The purpose of this paper is to promote a system dynamics-discrete event simulation (SD-DES) hybrid modelling framework, one that is useful for investigating problems comprising multifaceted elements which interact and evolve over time, such as is found in TPM. Design/methodology/approach The hybrid modelling framework commences with system observation using field notes which culminate in model conceptualization to structure the problem. Thereafter, an SD-DEShybrid model is designed for the system, and simulated to proffer improvement programmes. The hybrid model emphasises the interactions between key constructs relating to the system, feedback structures and process flow concepts that are the hallmarks of many problems in production. The modelling framework is applied to the TPM operations of a bottling plant where sub-optimal TPM performance was affecting throughput performance. Findings Simulation results for the case study show that intangible human factors such as worker motivation do not significantly affect TPM performance. What is most critical is ensuring full compliance to routine and scheduled maintenance tasks and coordinating the latter to align with rate of machine defect creation. Research limitations/implications The framework was developed with completeness, generality and reuse in view. It remains to be applied to a wide variety of TPM and non-TPM-related problems. Practical implications The developed hybrid model is scalable and can fit into an existing discrete event simulation model of a production system. The case study findings indicate where TPM managers should focus their efforts. Originality/value The investigation of TPM using SD-DES hybrid modelling is a novelty.

Network resilience modelling: a New Zealand forestry supply chain case

2020 ◽  
Vol 31 (2) ◽  
pp. 291-311
Author(s):  
Paul Childerhouse ◽  
Mohammed Al Aqqad ◽  
Quan Zhou ◽  
Carel Bezuidenhout
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Supply Chains ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Network Resilience ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Event Simulation ◽  
Export Supply

PurposeThe objective of this research is to model supply chain network resilience for low frequency high impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance supply chain resilience.Design/methodology/approachThe research models the resilience of New Zealand's log export logistical network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience of the nation's ports, then discrete event simulation is used to evaluate operational constraints and validate the capacity of operational flows from forests to ports.FindingsThe synthesis of linear programming and discrete event simulation provide a holistic approach to evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can be complimented with operational flexibility to enhance network resilience in the long term.Research limitations/implicationsThe two-tier modelling approach has only been applied to New Zealand's log export supply chains, so further applications are needed to insure reliability. The requirement for large quantities of empirical data relating to operational flows limited the simulation component to a single regionPractical implicationsNew Zealand's log export supply chain has low resilience; in most cases the closure of a port significantly constrains export capacity. Strategic selection of location and transportation mode by foresters and log exporters can significantly enhance the resilience of their supply chains.Originality/valueThe use of a two-tiered analytical approach enhances validity as each level's limitations and assumptions are addressed when combined with one another. Prior predominantly theoretical research in the field is validated by the empirical investigation of supply chain resilience.

Uncovering effective process improvement strategies in an emergency department using discrete event simulation

2014 ◽  
Vol 3 (2) ◽  
pp. 93-104 ◽  
Author(s):  
Oh Hong Choon ◽  
Zhang Dali ◽  
Phua Tien Beng ◽  
Chow Peck Yoke Magdalene
Keyword(s):  
Emergency Department ◽  
Discrete Event Simulation ◽  
Process Improvement ◽  
Discrete Event ◽  
Event Simulation ◽  
Improvement Strategies

scholarly journals Improving productivity of road surfacing operations using value stream mapping and discrete event simulation

2017 ◽  
Vol 17 (3) ◽  
pp. 294-323 ◽  
Author(s):  
Zeeshan Aziz ◽  
Rana Muhammad Qasim ◽  
Sahawneh Wajdi
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Primary Data ◽  
Value Stream Mapping ◽  
Research Approach ◽  
Production Rates ◽  
Related Factors ◽  
Content Type ◽  
Value Stream ◽  
Event Simulation

Purpose The purpose of this paper is to investigate the integration of discrete event simulation (DES) and value stream mapping (VSM) to enhance the productivity of road surfacing operations by achieving high production rates and minimum road closure times. Highway infrastructure is one of the most valuable assets owned by the public sector. The success of national and local economies as well as quality of life of the general public depend on the efficient operations of highways. Ensuring smooth traffic operations requires maintenance and improvements of the highest standard. Design/methodology/approach Research approach involved the use of primary data collected from direct observation, interviews, review of archival records and productivity databases. Based on this, process maps and value stream maps were developed which were subsequently used to produce discrete event simulation models for the exploration of different optimisation scenarios. Findings This research highlights the synergistic relationship between VSM and DES in driving innovation in construction processes. Identified factors that affect roadworks process productivity include machine, manpower, material, information, environment and method-related factors. A DES model is presented to optimise the process and increase the production rates. A hybrid DES-VSM approach ensures an integrated approach to process optimisation. Research limitations/implications This study is an application of hybrid version of previously published DES-VSM framework in the manufacturing sector. The present study has extended and tested its applicability within road surfacing operations. The different what-if scenarios presented in this paper might not be applicable to other parts of the world owing to various constraints. The study has focused on addressing the waste production inherent in pavement laying process. Even though external variables could possibly influence pavement process, those were ignored to allow for in-depth focus on the process under consideration. Practical implications Road users are one of the most important stakeholders that will benefit from the positive implications of this study. Private resurfacing companies and transport departments can optimise their overall process and style of working by comparing their end-to-end process and work plans with the ones mentioned in this paper. It will boost the productivity of equipment like planners, pavers and other machines used for resurfacing operations. Originality/value Existing approaches to process modelling such as VSM and process diagrams are constrained by their effectiveness in the analysis of dynamic and complex processes. This study presents a DES-based approach to validate targeted improvements of the current state of road surfacing processes and in exploration of different optimisation scenarios.

Improving materials logistics plan in road construction projects using discrete event simulation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amin Alvanchi ◽  
Farshid Baniassadi ◽  
Mahdi Shahsavari ◽  
Hamed Kashani
Keyword(s):  
Discrete Event Simulation ◽  
Construction Projects ◽  
Construction Material ◽  
Discrete Event ◽  
Road Construction ◽  
Combinatorial Problem ◽  
The Body ◽  
Content Type ◽  
Event Simulation ◽  
Material Sources

PurposeMotivated by the high cost of material movements in road construction projects, past studies have used analytical methods to optimize materials logistics plans. A key shortcoming of these methods is their inability to capture the uncertain, dynamic and complex characteristics of the road construction material logistics. Failure to incorporate these characteristics can lead to sub-optimal results. The purpose of this study is to propose the use of discrete event simulation (DES) to address the existing shortfall.Design/methodology/approachDespite the powerful capabilities of DES models in capturing the operational complexities of construction projects, they have not been previously utilized to optimize the material logistics of road construction projects. The proposed DES-based method in this research captures the operational details of material logistics and uses a heuristic approach to overcome the combinatorial problem of numerous choices. The method was applied to a 63.5 km real-world road construction project case to demonstrate its capabilities.FindingsSix different material types from 28 material sources were used in the case. Approximately 1.5% of the material logistics costs were saved by following the proposed method and choosing appropriate material sources.Originality/valueThis research contributes to the body of knowledge by leveraging the capabilities of DES and presenting a novel method for improving the materials logistics plan of road construction projects. The proposed method provides practitioners with the basis for capturing the key operational details that were overlooked in the past. The proposed method can be adopted in road construction projects to reduce the overall material procurement cost.

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