Simulation in industry 4.0: A state-of-the-art review de Paula Ferreira, William; Armellini, Fabiano; De Santa-Eulalia, Luis Antonio
Computers & industrial engineering,
November 2020, 2020-11-00, Volume:
149
Journal Article
Peer reviewed
Open access
Simulation is a key technology for developing planning and exploratory models to optimize decision making as well as the design and operations of complex and smart production systems. It could also ...aid companies to evaluate the risks, costs, implementation barriers, impact on operational performance, and roadmap toward Industry 4.0. Although several advances have been made in this domain, studies that systematically characterize and analyze the development of simulation-based research in Industry 4.0 are scarce. Therefore, this study aims to investigate the state-of-the-art research performed on the intersecting area of simulation and the field of Industry 4.0. Initially, a conceptual framework describing Industry 4.0 in terms of enabling technologies and design principles for modeling and simulation of Industry 4.0 scenarios is proposed. Thereafter, literature on simulation technologies and Industry 4.0 design principles is systematically reviewed using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. This study reveals an increasing trend in the number of publications on simulation in Industry 4.0 within the last four years. In total, 10 simulation-based approaches and 17 Industry 4.0 design principles were identified. A cross-analysis of concepts and evaluation of models’ development suggest that simulation can capture the design principles of Industry 4.0 and support the investigation of the Industry 4.0 phenomenon from different perspectives. Finally, the results of this study indicate hybrid simulation and digital twin as the primary simulation-based approaches in the context of Industry 4.0.
•Presents a conceptual framework for modeling and simulation of Industry 4.0 scenarios.•Describe 10 simulation-based approaches being employed in the context of Industry 4.0.•Identifies 17 design principles of Industry 4.0.•Establishes a link between simulation technologies and the design principles of Industry 4.0.•Provides a comprehensive classification of simulation in the context of Industry 4.0.
We present the R package SimInf which provides an efficient and very flexible framework to conduct data-driven epidemiological modeling in realistic large scale disease spread simulations. The ...framework integrates infection dynamics in subpopulations as continuous-time Markov chains using the Gillespie stochastic simulation algorithm and incorporates available data such as births, deaths and movements as scheduled events at predefined time-points. Using C code for the numerical solvers and divide work over multiple processors ensures high performance when simulating a sample outcome. One of our design goals was to make SimInf extendable and enable usage of the numerical solvers from other R extension packages in order to facilitate complex epidemiological research. In this paper, we provide a technical description of the framework and demonstrate its use on some basic examples. We also discuss how to specify and extend the framework with user-defined models.
Understanding design complexity for additive manufacturing (AM) is essential in AM production planning since conventional make-to-order production for individual AM orders of complex designs can ...amplify operational uncertainty in an entire AM production system. As a response, this study aims not only to demonstrate the impact of design complexity on AM production but also to propose a novel order dispatching approach based on design complexity that mitigates operational uncertainty in an AM production system. First, a design complexity measure was developed using an information theoretic approach. Next, a discrete-event simulation model to represent an AM production system consisting of parallel AM machines for jet-engine bracket designs was built to identify the impact of design complexity on average order lead time and total production cost through regressions. Finally, a flexible order dispatching rule that reflects operational attitudes toward design complexity was proposed to determine part-processing priorities by tracking both part- and system-level design complexity states in a centralized queue for AM production. The proposed dispatching rule was compared with relevant static dispatching rules to assess its performance in operational efficiency under varied attitudes toward design complexity. The findings from this study clearly showed the negative impact of design complexity on operational performance for AM production. Moreover, the proposed dispatching rule resulted in lead time reduction and balanced lead time performance in AM production against alternative static dispatching strategies. This study demonstrates the importance of design complexity-based flexible operations to properly handle latent uncertainties in an AM production system.
•Characterization of design complexity for additive manufacturing (AM) as a measure.•Development of design complexity-based flexible order dispatching for AM production.•Simulated flexible vs. static order dispatching to compare production efficiency.•The negative impact of design complexity is identified in a make-to-order AM system.•The proposed approach shows better production efficiency and balanced lead time.
•Sanitizer depletion is a major cause of failures in automatic sanitizer dispensers.•Refill service alert can greatly reduce the chances of sanitizer depletion.•The energy design of a sanitizer ...dispenser affects its hand hygiene performance.•Machine learning techniques can improve the speed and accuracy of simulation.
Automatic dispensers of alcohol-based handrub (ABHR) have been widely adopted in healthcare facilities to maintain hand hygiene (HH). A proper supply of energy and refill is crucial to ensure uninterrupted access to hand sanitizing and minimize workflow disruption and inefficiencies. Various energy design and refill replenishment technologies have emerged with promising potential to eliminate HH disruptions. However, there is a lack of quantitative studies assessing the design impact on hand hygiene performance in healthcare settings. In this paper, we employ data-driven discrete-event simulation (DES) to evaluate the long-term performance of various energy designs of automatic dispensers in healthcare facilities. We analyze 7 years of historical usage data from 4 US hospitals and identify the usage patterns, which serve as the input traffic for our simulation model. We then estimate the workflow disruption caused by different types of dispensers over a 6-year period, in terms of the number of missed HH opportunities, battery replacements, and duration of downtime. The simulation results suggest that the differences in performance are significant among dispenser types. In high usage, the number of missed HH opportunities caused by refill depletion ranges from 403.1 to 1232.4, and total downtime ranges from 0 to 96.3 h. Implementing proactive maintenance measures, such as service refill alerts, can greatly reduce the chances of ABHR depletion, resulting an 81.6 % decrease in HH disruptions for a single dispenser in high usage. Therefore, healthcare facilities should consider the variations in dispenser design, including the energy management system. They should also carefully study dispenser usage patterns to implement optimized policies and practices for ABHR refill maintenance to minimize overall missed HH opportunities.
•Hybrid simulation is a new but rapidly growing area in operational research.•The main application areas are healthcare, manufacturing and supply chains.•There are many technical and methodological ...challenges.•Major research opportunities in conceptual modelling and validation.•This paper presents a life-cycle based framework to guide modellers and authors.
Hybrid simulation (defined as a modelling approach that combines two or more of the following methods: discrete-event simulation, system dynamics, and agent-based simulation) has experienced near-exponential growth in popularity in the past two decades. However, a large proportion of the academic literature on hybrid simulation is found in computer science and engineering journals. Given the importance of this emerging area and its relevance to operational research, this paper provides a review of the topic from an OR perspective. The results of a review of the hybrid simulation literature are presented, using a novel framework based on the simulation lifecycle that will be useful for future modellers and authors alike. Promising areas for future research are identified: these include the development of new methods for conceptual modelling and for model validation. Currently the main application areas are healthcare, supply chain management and manufacturing, and the majority of published models combine discrete-event simulation and system dynamics.
In this paper, we studied a production line of a mattress manufacturing company. A simulation model was modeled in ARENA ® to evaluate the current production process and formulate proposals for ...improvement. Several scenarios were tested with the validated model, concluding with two proposals—first, a new method for the sheet lining process that allows reducing the resources required, and second, hiring two material handlers to transport the work in process between workstations. Based on our simulation results, the proposed improvements increase overall productivity and satisfy the expected demand.
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