A Shipyard Simulation System using the Process-centric Simulation Modeling Methodology: Case Study of the Simulation Model for the Shipyard Master Plan Validation

2016 ◽  
Vol 21 (2) ◽  
pp. 204-214 ◽  
Author(s):  
Yong-Kuk Jeong ◽  
Jong-Hun Woo ◽  
Dae-Kyun Oh ◽  
Jong-Gye Shin
Keyword(s):  
Simulation Model ◽  
Simulation Modeling ◽  
Simulation System ◽  
Master Plan ◽  
Modeling Methodology

scholarly journals Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study

2021 ◽  
Vol 11 (8) ◽  
pp. 3487
Author(s):  
Helge Nordal ◽  
Idriss El-Thalji
Keyword(s):  
Simulation Model ◽  
Simulation Modeling ◽  
Study Data ◽  
Opportunistic Maintenance ◽  
Maintenance Strategies ◽  
Modeling Approach ◽  
Intelligent Maintenance ◽  
Diagnosis And Prognosis ◽  
Case Study Data

The introduction of Industry 4.0 is expected to revolutionize current maintenance practices by reaching new levels of predictive (detection, diagnosis, and prognosis processes) and prescriptive maintenance analytics. In general, the new maintenance paradigms (predictive and prescriptive) are often difficult to justify because of their multiple inherent trade-offs and hidden systems causalities. The prediction models, in the literature, can be considered as a “black box” that is missing the links between input data, analysis, and final predictions, which makes the industrial adaptability to such models almost impossible. It is also missing enable modeling deterioration based on loading, or considering technical specifications related to detection, diagnosis, and prognosis, which are all decisive for intelligent maintenance purposes. The purpose and scientific contribution of this paper is to present a novel simulation model that enables estimating the lifetime benefits of an industrial asset when an intelligent maintenance management system is utilized as mixed maintenance strategies and the predictive maintenance (PdM) is leveraged into opportunistic intervals. The multi-method simulation modeling approach combining agent-based modeling with system dynamics is applied with a purposefully selected case study to conceptualize and validate the simulation model. Three maintenance strategies (preventive, corrective, and intelligent) and five different scenarios (case study data, manipulated case study data, offshore and onshore reliability data handbook (OREDA) database, physics-based data, and hybrid) are modeled and simulated for a time period of 20 years (175,200 h). Intelligent maintenance is defined as PdM leveraged in opportunistic maintenance intervals. The results clearly demonstrate the possible lifetime benefits of implementing an intelligent maintenance system into the case study as it enhanced the operational availability by 0.268% and reduced corrective maintenance workload by 459 h or 11%. The multi-method simulation model leverages and shows the effect of the physics-based data (deterioration curves), loading profiles, and detection and prediction levels. It is concluded that implementing intelligent maintenance without an effective predictive horizon of the associated PdM and effective frequency of opportunistic maintenance intervals, does not guarantee the gain of its lifetime benefits. Moreover, the case study maintenance data shall be collected in a complete (no missing data) and more accurate manner (use hours instead of date only) and used to continuously upgrade the failure rates and maintenance times.

scholarly journals Rapid-cycle systems modeling to support evidence-informed decision-making during system-wide implementation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
R. Christopher Sheldrick ◽  
Gracelyn Cruden ◽  
Ana J. Schaefer ◽  
Thomas I. Mackie
Keyword(s):  
Simulation Model ◽  
Simulation Modeling ◽  
Implementation Strategy ◽  
Simulation Models ◽  
Illustrative Case ◽  
Systems Modeling ◽  
Cycle Systems ◽  
Analytic Strategy ◽  
Group Interviews

Abstract Background To “model and simulate change” is an accepted strategy to support implementation at scale. Much like a power analysis can inform decisions about study design, simulation models offer an analytic strategy to synthesize evidence that informs decisions regarding implementation of evidence-based interventions. However, simulation modeling is under-utilized in implementation science. To realize the potential of simulation modeling as an implementation strategy, additional methods are required to assist stakeholders to use models to examine underlying assumptions, consider alternative strategies, and anticipate downstream consequences of implementation. To this end, we propose Rapid-cycle Systems Modeling (RCSM)—a form of group modeling designed to promote engagement with evidence to support implementation. To demonstrate its utility, we provide an illustrative case study with mid-level administrators developing system-wide interventions that aim to identify and treat trauma among children entering foster care. Methods RCSM is an iterative method that includes three steps per cycle: (1) identify and prioritize stakeholder questions, (2) develop or refine a simulation model, and (3) engage in dialogue regarding model relevance, insights, and utility for implementation. For the case study, 31 key informants were engaged in step 1, a prior simulation model was adapted for step 2, and six member-checking group interviews (n = 16) were conducted for step 3. Results Step 1 engaged qualitative methods to identify and prioritize stakeholder questions, specifically identifying a set of inter-related decisions to promote implementing trauma-informed screening. In step 2, the research team created a presentation to communicate key findings from the simulation model that addressed decisions about programmatic reach, optimal screening thresholds to balance demand for treatment with supply, capacity to start-up and sustain screening, and availability of downstream capacity to provide treatment for those with indicated need. In step 3, member-checking group interviews with stakeholders documented the relevance of the model results to implementation decisions, insight regarding opportunities to improve system performance, and potential to inform conversations regarding anticipated implications of implementation choices. Conclusions By embedding simulation modeling in a process of stakeholder engagement, RCSM offers guidance to realize the potential of modeling not only as an analytic strategy, but also as an implementation strategy.

Impact of merger on efficiency and productivity : a case study of commercial banks in Malaysia

1970 ◽  
Vol 5 (1) ◽  
pp. 77
Author(s):  
Mahadzir Ismail ◽  
Saliza Sulaiman ◽  
Hasni Abdul Rahim ◽  
Nordiana Nordin
Keyword(s):  
Efficiency Score ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment ◽  
Master Plan ◽  
Before And After ◽  
Domestic Banks ◽  
The Impact ◽  
Efficiency And Productivity

The Financial Master Plan (2001- 2010) aims to enhance the capacity of banking industry so that higher effic iency and productivity can be reaped in the future. This study seeks to determine the impact of merger on the efficiency and productivity ofcommercial banks in Malaysia for the period 1995 until 2005. The study uses a non-parametric approach, nam ely DEA (data envelopment analysis?) to estimate the efficiency scores and to construct the Malmquist productivity index. To enable this estimation, three bank inputs and outputs are used. Amongst the findings are those banks exhibit higher efficiency score after the merger and thefo reign banks are more efficient than the local banks. Productivity of the banks is calculated in both periods, before and after the merger: The results show that, it is the local banks that have improved the most after the merger. The main source of productivity is technical change or innovation. The findings support the existing policy of having larger domestic banks in term of size.

EVALUASI PROYEKSI DEMAND BARANG DAN PENUMPANG PELABUHAN DI PROVINSI MALUKU

2019 ◽  
Vol 19 (2) ◽  
pp. 101-110
Author(s):  
Adrian Firdaus ◽  
M. Dwi Yoga Sutanto ◽  
Rajin Sihombing ◽  
M. Weldy Hermawan
Keyword(s):  
Time Series ◽  
Projection Method ◽  
Development Plan ◽  
Master Plan ◽  
Port Development ◽  
Loading And Unloading ◽  
The Difference ◽  
Existing Data

Abstract Every port in Indonesia must have a Port Master Plan that contains an integrated port development plan. This study discusses one important aspect in the preparation of the Port Master Plan, namely the projected movement of goods and passengers, which can be used as a reference in determining the need for facilities at each stage of port development. The case study was conducted at a port located in a district in Maluku Province and aims to evaluate the analysis of projected demand for goods and passengers occurring at the port. The projection method used is time series and econometric projection. The projection results are then compared with the existing data in 2018. The results of this study show that the econometric projection gives adequate results in predicting loading and unloading activities as well as the number of passenger arrival and departure in 2018. This is indicated by the difference in the percentage of projection results towards the existing data, which is smaller than 10%. Whereas for loading and unloading activities, time series projections with logarithmic trends give better results than econometric projections. Keywords: port, port master plan, port development, unloading activities  Abstrak Setiap pelabuhan di Indonesia harus memiliki sebuah Rencana Induk Pelabuhan yang memuat rencana pengem-bangan pelabuhan secara terpadu. Studi ini membahas salah satu aspek penting dalam penyusunan Rencana Induk Pelabuhan, yaitu proyeksi pergerakan barang dan penumpang, yang dapat dipakai sebagai acuan dalam penentuan kebutuhan fasilitas di setiap tahap pengembangan pelabuhan. Studi kasus dilakukan pada sebuah pelabuhan yang terletak di sebuah kabupaten di Provinsi Maluku dan bertujuan untuk melakukan evaluasi ter-hadap analisis proyeksi demand barang dan penumpang yang terjadi di pelabuhan tersebut. Metode proyeksi yang dipakai adalah proyeksi deret waktu dan ekonometrik. Hasil proyeksi selanjutnya dibandingkan dengan data eksisting tahun 2018. Hasil studi ini menunjukkan bahwa proyeksi ekonometrik memberikan hasil yang cukup baik dalam memprediksi aktivitas bongkar barang serta jumlah penumpang naik dan turun di tahun 2018. Hal ini diindikasikan dengan selisih persentase hasil proyeksi terhadap data eksisting yang lebih kecil dari 10%. Sedangkan untuk aktivitas muat barang, proyeksi deret waktu dengan tren logaritmik memberikan hasil yang lebih baik daripada proyeksi ekonometrik. Kata-kata kunci: pelabuhan, rencana induk pelabuhan, pengembangan pelauhan, aktivitas bongkar barang

SIMULATION OF A SEA CARGO PORT AS A QUEUING SYSTEM IN ANYLOGIC

2020 ◽  
Vol 4 (26) ◽  
pp. 59-66
Author(s):  
A. G. Morozkov ◽  
◽  
M. R. Yazvenko ◽  
Keyword(s):  
Simulation Model ◽  
Key Words ◽  
Simulation Modeling ◽  
Queue Length ◽  
System Simulation ◽  
Queuing System ◽  
System Model ◽  
System Capacity ◽  
Mathematical Solution ◽  
Structure Simulation

The article presents simplified queuing system model of freight marine port. The article discusses the basic elements of queuing system, its mathematical solution and structure. Simulation model was created using AnyLogic to analyze an effect of system capacity on queue length. The results were analyzed and the solution for queue optimization was proposed. Key words: queuing system, simulation modeling, AnyLogic, marine port, servers, queue.

E-Gov Master Plan (Case Study: XYZ City)

2020 ◽  
Vol 24 (02) ◽  
pp. 3180-3185
Author(s):  
Sri Lestari ◽  
Iwan Rijayana ◽  
Rae Virgana ◽  
Murnawan ◽  
Ucu Nugraha ◽  
...  
Keyword(s):  
Master Plan

Optimization of the Navy’s three-dimensional mine impact burial prediction simulation model, Impact35, using high-order numerical methods

2021 ◽  
pp. 154851292110286
Author(s):  
Athanasios Donas ◽  
Ioannis Famelis ◽  
Peter C Chu ◽  
George Galanis
Keyword(s):  
Numerical Analysis ◽  
Numerical Methods ◽  
Prediction Model ◽  
Simulation Model ◽  
Three Dimensional ◽  
Simulation System ◽  
High Order ◽  
Alternative Methodology ◽  
Runge Kutta ◽  
Fifth Order

The aim of this paper is to present an application of high-order numerical analysis methods to a simulation system that models the movement of a cylindrical-shaped object (mine, projectile, etc.) in a marine environment and in general in fluids with important applications in Naval operations. More specifically, an alternative methodology is proposed for the dynamics of the Navy’s three-dimensional mine impact burial prediction model, Impact35/vortex, based on the Dormand–Prince Runge–Kutta fifth-order and the singly diagonally implicit Runge–Kutta fifth-order methods. The main aim is to improve the time efficiency of the system, while keeping the deviation levels of the final results, derived from the standard and the proposed methodology, low.

Multi-scale flooding hazards evaluation using a nested flood simulation model: Case study of Jamuna River, Bangladesh

2021 ◽  
pp. 1-38
Author(s):  
Masakazu Hashimoto ◽  
Kenji Kawaike ◽  
Tomonori Deguchi ◽  
Shammi Haque ◽  
Arpan Paul ◽  
...  
Keyword(s):  
Simulation Model ◽  
Model Case ◽  
Flood Simulation ◽  
Multi Scale ◽  
Flooding Hazards

Automation Master Plan Framework: Case Study

2012 ◽  
Author(s):  
David Herrera ◽  
Jose Avelino ◽  
Joaquin Sanchez ◽  
Oscar Diaz ◽  
Abraham Galan ◽  
...  
Keyword(s):  
Master Plan
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