Search results

The purpose of this paper is to provide a simulation model for assessing innovation deployment strategies by evaluating and comparing their outcomes using a hybrid modeling and simulation of agent‐based modelling and simulation (ABMS) and system dynamics (SD). Since successful deployment of innovations in any organization is as important as the innovations themselves, how to choose a suitable deployment strategy and assess its effectiveness before actual implementation is a critical task.

This paper adopts a hybrid modeling and simulation approach combining the advantages of agent‐based modeling and system dynamics to study the activities and strategies involved in innovation deployment. The developed model was verified and validated with the data from GM's OnStar project.

The research demonstrates that evaluating various deployment strategies for desirable results through hybrid modeling and simulation is possible and useful by finding critical factors and making appropriate forecast, which would aid managers in assessment of innovation deployment strategies and deployment decision‐making processes.

The hybrid modeling and simulation approach provides a powerful tool in various study fields, not only in industries, but also suitable to evaluate the system outputs in both macroscopic and microscopic point of view for many strategy‐making or consulting firms. The presented work is meant for proof‐of‐concept, so numerous expansions are necessary for use in different projects.

For the case evaluated in this paper, it is found that a customer‐oriented strategy outperforms a cost‐oriented strategy in market share as well as customer satisfaction and profit. Cooperation and R&D are essential innovation drivers, but from the study, customer satisfaction does not solely depend on technical advantages. Alliance is a key factor to reduce the cost and risk of uncertainties. The structure and approach of the presented hybrid simulation model can be adopted for other cases to derive conclusions.

The originality of the paper lies in the way of adopting a hybrid modeling and simulation approach to study the effects of innovation deployment strategies. The model can be modified and used in a wide range of organizations to evaluate different strategies and aid decision‐making processes.

Construction planning for microtunneling projects is a complex process due to the high level of uncertainties inherent in underground construction and the interdependent nature of decision variables. Simulation is a suitable decision-making tool to account for uncertainties and to model complex dependencies among decision variables. This paper aims to improve microtunneling construction planning by using simulation.

This study proposes a hybrid simulation approach that combines discrete event simulation (DES) with continuous simulation (CS) for microtunneling construction planning. In this approach, DES is used to model construction processes at the activity level and CS is used to model the continuous flow of soil material in the system.

To demonstrate the capability of the proposed approach in construction planning of microtunneling projects, different construction plan scenarios are compared in a microtunneling case study. The results of the case study show suitability of the hybrid DES-CS approach in simulating microtunneling construction processes and the practicality of the approach for identifying the most efficient construction plan.

This study proposes a new modeling approach for microtunneling construction processes using hybrid simulation and provides decision support at the construction planning stage of projects.

With hybrid simulation techniques getting popular for systems improvement in multiple fields, this study aims to provide insight on the use of hybrid simulation to assess the effect of lean manufacturing (LM) techniques on manufacturing facilities and the transition of a mass production (MP) facility to incorporating LM techniques.

In this paper, the authors apply a hybrid simulation approach to improve an educational automotive assembly line and provide guidelines for implementing different LM techniques. Specifically, the authors describe the design, development, verification and validation of a hybrid discrete-event and agent-based simulation model of a LEGO® car assembly line to analyze, improve and assess the system’s performance. The simulation approach examines the base model (MP) and an alternative scenario (just-in-time [JIT] with Heijunka).

The hybrid simulation approach effectively models the facility. The alternative simulation scenario (implementing JIT and Heijunka LM techniques) improved all examined performance metrics. In more detail, the system’s lead time was reduced by 47.37%, the throughput increased by 5.99% and the work-in-progress for workstations decreased by up to 56.73%.

This novel hybrid simulation approach provides insight and can be potentially extrapolated to model other manufacturing facilities and evaluate transition scenarios from MP to LM.

This study aims to seek to advance a system dynamics-discrete event hybrid simulation modelling concept useful for taking improvement decisions where one needs to consider the interactions between human factors and process flow elements in lean manufacturing systems.

A unique approach is taken to hybrid simulation modelling where the whole problem situation is first conceptualized using a causal loop diagram and stock and flow diagram, before transmitting to a hybrid simulation model. The concept is intended to simplify the simulation modelling process and make the concept pliable for use in various types of lean manufacturing problem situations.

The hybrid simulation modelling concept was applied to a lean manufacturing case where quality performance was sporadic mainly because of production pressures. The hybrid modelling concept revealed a solution that advanced full compliance with lean and one that required changes in job scheduling policies to promote both continuous improvement and throughput increases.

Because non-tangible aspects of lean were objectively assessed using the hybrid modelling concept, the study is an advancement towards establishing a credible link between human resource aspects of lean and the performance of an organization.

The applied hybrid model enabled managers in the plant navigate the trade-off decision they often face when choosing to advance production output ahead of continuous improvement practices.

System dynamics-discrete event hybrid simulation modelling is a rarity in lean manufacturing systems.

This paper aims to explore the applicability and strengths of proposing the three-paradigm hybrid simulation (HS) approach to developing and analysing strategies. The objective of the modelling effort is to conceptually illustrate its use in strategic planning by combining with the threat-opportunity-weakness-strength (TOWS) matrix, which builds a bridge between strategic management with the operations research community. The authors also aim to introduce a modelling framework to help model designers to apply HS to their own business issues.

The paper presents a process to develop a HS model associated with the development of strategies using the TOWS matrix.

After developing the model and testing four strategies, the best option for the supermarket to increase market share and sales is implementing the strength–opportunity strategy, which involves online shopping to adapt to the digital world.

First, some modelling assumptions are used to simplify the development process, but they need further validation. Second, the real data collection is limited. Third, the personal learning edition of the simulation software is not a comprehensive version and has some limitations.

The hybrid model and the scenario planning introduced, in this study, could allow decision makers to rehearse the potential strategy before actual implementation. The framework is easy to implement to other business and industry.

This study links HS with strategic management, which has not been performed previously and evaluates the capability of HS in strategic planning. The functionality of the modelling platform has been tested for simulating a completely dynamic system.

Petri net (PN) and queuing theory are used in performance analysis of a flexible manufacturing system (FMS). They are used to determine the FMS measures of performance. These measures of performance include optimal work‐in‐process (WIP), lead time, production rate, machine utilization, and number of servers at each station. The purpose of this paper is to present a comparison between PN and queuing network tools to determine the optimum values for FMS measures of performance.

PN model with dual kanban and closed queuing network are used for analysis and performance evaluation of FMS. Integrated network analyzer and Lingo softwares are used for performance evaluation of FMS by PN tool. CANQ software is used for performance evaluation of FMS by queuing network. In both the approaches, the throughput is bounded by the utilization of the bottleneck machines.

The comparison shows that for the given number of servers, PN gives better values of performance measures for FMS. The PN optimization gives minimum WIP corresponding to the maximum production rate. Minimum WIP leads to minimum lead time.

The results are concluded based on one case study. In future research, the results may be achieved by doing more case studies with different numbers of system parameters and/or parameter settings.

Using the PN model, the production manager may design, analyze, evaluate, and even optimize the layout of the production system for minimum WIP, maximum throughput, and reduced lead time. The determination of the total WIP, total number of stations in the production system, and the number of servers at each station may be helpful in shop floor management. It may result in more production efficiency along with ease of supervision.

This paper presents a first novel comparison of its kind between PN and queuing network for evaluation of FMS.

Dynamic planning and scheduling forms a widely adopted smart strategy for solving real-world problems in diverse business systems. This paper uses deductive content analysis to explore secondary data from previous studies in dynamic planning and scheduling to draw conclusions on its current status, forward action and research needs in construction management.

The authors searched academic databases using planning and scheduling keywords without a periodic setting. This research collected secondary data from the database to draw an objective comparison of categories and conclusions about how the data relates to planning and scheduling to avoid the subjective responses from questionnaires and interviews. Then, applying inclusion and exclusion criteria, we selected one hundred and four articles. Finally, the study used a seven-step deductive content analysis to develop the categorisation matrix and sub-themes for describing the dynamic planning and scheduling categories. The authors used deductive analysis because of the secondary data and categories comparison. Using the event types represented in a quadrant mapping, authors delve into where, when, application and benefits of the classes.

The content analysis showed that all the accounts and descriptions of dynamic planning and scheduling are identifiable in an extensive research database. The content analysis reveals the need for multi-hybrid (4D BIM-Agent based-discrete event-discrete rate-system dynamics) simulation modelling and optimisation method for proffering solutions to scheduling and planning problems, its current status, tools and obstacles.

This research reveals the deductive content analysis talent in construction research. It also draws direction, focuses and raises a question on dynamic planning and scheduling research concerning the five-integrated model, an opportunity for their integration, models combined attributes and insight into its solution viability in construction.

Recently, much research about the effects of simulation on an organization’s operational performance and efficiency has been carried out. But still, there is a need for lean-based simulations rather than just modelling the system. However, these studies still lack systematization. Consequently, the purpose of this paper is to systematize the literature on lean simulations in the area of production and operations management.

A systematic analysis was performed on 93 articles extracted from the Clarivate Analytics Web of Science (WoS) Core Collection database. The analysis was limited to only articles that come under the “Engineering industrial,” “Engineering Manufacturing” and “Operations Research and Management” subject category in WoS Core Collection database. Later, a bibliometric analysis was integrated with the literature review for deeper literature categorization.

A bibliometric analysis displayed the relevance of selected literature (keywords, authors and sources). The systematic literature review helped to clarify each clusters’ content and purpose.

This study portrays the gaps in the lean simulation integration methods and techniques through a detailed systematic and bibliometric review.

Lean managers can get various insights and ideas on implementing lean and simulation integration methods in real-time process improvement scenarios.

This study demonstrates the best future recommendations for lean based modelling for both consumers and organizations that shall address the social and economic issues.

To the best of the authors’ knowledge, minimal attention has been paid to systematizing the literature on lean simulation in industrial, manufacturing and operations management. This study contributes to close this gap.

In the hybrid electricity market consisting of renewable and conventional energy, the generation output of renewable power is uncertain because of its intermittency, and the power market demand is also fluctuant. Meanwhile, there is fierce competition among power producers in the power supply market and retailers in the demand market after deregulation, which increases the difficulty of renewable energy power grid-connection. To promote grid-connection of renewable energy power in the hybrid electricity market, the authors construct different contract decision-making models in the “many-to-many” hybrid power supply chain to explore the pricing strategy of renewable energy power grid-connecting.

Considering the dual-uncertainty of renewable energy power output and electricity market demand, the authors construct different decision-making models of wholesale price contract and revenue-sharing contract to compare and optimize grid-connecting pricing, respectively, to maximize the profits of different participants in the hybrid power supply chain. Besides, the authors set different parameters in the models to explore the influence of competition intensity, government subsidies, etc. on power pricing. Then, a numerical simulation is carried out, they verify the existence of the equilibrium solutions satisfying the supply chain coordination, compare the differences of pricing contracts and further analyze the variation characteristics of optimal contract parameters and their interaction relations.

Revenue-sharing contract can increase the quantity of green power grid-connection and realize benefits Pareto improvement of all parties in hybrid power supply chain. The competition intensity both of power supply and demand market will have an impact on the sharing ratio, and the increase of competition intensity results in a reduction of power supply chain coordination pressure. The power contract price, spot price and selling price have all been reduced with the increase of the sharing ratio, and the price of renewable power is more sensitive to the ratio change. The sharing ratio shows a downward trend with the increase of government green power subsidies.

On the basis of expanding the definition of hybrid power market and the theory of newsvendor model, considering the dual-uncertainty of green power generation output and electricity market demand, this paper builds and compares different contract decision-making models to study the grid-connection pricing strategy of renewable energy power. And as an extension of supply chain structure types and management, the authors build a “many-to-many” power supply chain structure model and analyze the impact of competition intensity among power enterprises and the government subsidy on the power grid-connecting pricing.