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

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.

Procedia CIRP ◽  
2018 ◽  
Vol 72 ◽  
pp. 1536-1541 ◽  
Author(s):  
Daniel Nåfors ◽  
Maja Bärring ◽  
Maxime Estienne ◽  
Björn Johansson ◽  
Mats Wahlström

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 816 ◽  
Author(s):  
Emad Alzubi ◽  
Anas M. Atieh ◽  
Khaleel Abu Shgair ◽  
John Damiani ◽  
Sima Sunna ◽  
...  

This paper studies manufacturing processes in a wooden furniture manufacturing company. The company suffers from long manufacturing lead times and an unbalanced production line. To identify sources of waste and delay value stream mapping (VSM) and a discrete event simulation model is implemented. VSM is used to visualize and analyze the major processes of the company and provide quantifiable KPIs; the manufacturing lead-time and then Overall Equipment Effectiveness (OEE) settings. A discrete event simulation model is then built to analyze the company on a wider scale and provide the data required to identify bottlenecks. Building on the data gathered from the production lines and the simulation model, two-bottleneck detection methods are used, the utilization method, and the waiting time method. Then based on the comparison of the two methods a third bottleneck detection is utilized; the scenario-based method, to identify the primary and secondary bottlenecks. After the bottlenecks are identified, changes are then evaluated using the simulation model and radar charts were built based on the improved simulation model, which evaluates the effect of changes in the utilization and OEE results. This work managed to neutralize the effect of one of the main bottlenecks and minimize the effect of the other. The manufacturing utilization was increased by 15.8% for the main bottleneck resources followed by 2.4% for the second one. However, it is hard to convince the traditional administration of this small size manufacturing plant to adopt a completely revolutionizing, costly, and risky (at such level) lean manufacturing approach. This paper studies and provides a much lower in cost and verified scheme of enhancement.


2016 ◽  
Vol 7 (1) ◽  
pp. 35-61 ◽  
Author(s):  
Stephan J. de Jong ◽  
Wouter W.A. Beelaerts van Blokland

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.


2016 ◽  
Vol 29 (7) ◽  
pp. 733-743 ◽  
Author(s):  
Kenneth Yip ◽  
Suk-King Pang ◽  
Kui-Tim Chan ◽  
Chi-Kuen Chan ◽  
Tsz-Leung Lee

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carolina Reis Gualberto ◽  
Lásara Fabrícia Rodrigues ◽  
Karine Araújo Ferreira

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.


2019 ◽  
Vol 25 (3) ◽  
pp. 476-498 ◽  
Author(s):  
Omogbai Oleghe ◽  
Konstantinos Salonitis

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.


2020 ◽  
Vol 31 (2) ◽  
pp. 291-311
Author(s):  
Paul Childerhouse ◽  
Mohammed Al Aqqad ◽  
Quan Zhou ◽  
Carel Bezuidenhout

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.


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