The wave energy converter control competition (WECCCOMP): Wave energy control algorithms compared in both simulation and tank testing

The wave energy control competition established a benchmark problem which was offered as an open challenge to the wave energy system control community. The competition had two stages: In the first stage, competitors used a standard wave energy simulation platform (WEC-Sim) to evaluate their controllers while, in the second stage, competitors were invited to test their controllers in a real-time implementation on a prototype system in a wave tank. The performance function used was based on converted energy across a range of standard sea states, but also included aspects related to economic performance, such as peak/average power, peak force, etc. This paper compares simulated and experimental results and, in particular, examines if the results obtained in a linear system simulation are borne out in reality. Overall, within the scope of the device tested, the range of sea states employed, and the performance metric used, the conclusion is that high-performance WEC controllers work well in practice, with good carry-over from simulation to experimentation. However, the availability of a good WEC mathematical model is deemed to be crucial

IMPROVING OF MANUFACTURING PRODUCTIVITY THROUGH SIMULATION

Improvement of manufacturing system is must do process due to development of manufacturing technology and increase in customer needs. Due to development of technology, companies need to do improvement of their current system in order to survive in competition. This study will analyse overall productivity and identified critical process that consider bottleneck. This study also will quantify impact of batch capacity in manufacturing productivity. Computer aided simulation software will be used as main method. Data of manufacturing system will be collected and will be used as input in simulation software.. Altering several parameters such as machines quantity and batch size helps author to studied final output. It helps author reduce time to do trial for new design as simulation software will done based on real time and system performance will be address to help improvise new design. Simulation also can be applied at both the justification phase and design phase. By using this method, critical area can be identified in manufacturing system and explore several solution based on different scenario

IMPROVING OF MANUFACTURING PRODUCTIVITY THROUGH SIMULATION

Improvement of manufacturing system is must do process due to development of manufacturing technology and increase in customer needs. Due to development of technology, companies need to do improvement of their current system in order to survive in competition. This study will analyse overall productivity and identified critical process that consider bottleneck. This study also will quantify impact of batch capacity in manufacturing productivity. Computer aided simulation software will be used as main method. Data of manufacturing system will be collected and will be used as input in simulation software.. Altering several parameters such as machines quantity and batch size helps author to studied final output. It helps author reduce time to do trial for new design as simulation software will done based on real time and system performance will be address to help improvise new design. Simulation also can be applied at both the justification phase and design phase. By using this method, critical area can be identified in manufacturing system and explore several solution based on different scenario

Big Data and Simulation In Lean Manufacturing From The Industry 4.0 Perspective

Among industry players, the success rate with the adoption of Lean Manufacturing (LM) has been growing significantly year-over-year, by leveraging the Industrial Revolution of 4.0. The boom in Industry 4.0 has resulted in exponential data growth in all fields. This has been possible due to the big data exchange system in real-time, which enables engineers to gain complete control of the system to deal with any forthcoming situation, including data collection and machine control. This scenario also results in competition encouraging the manufacturing industry to grow, thereby increasing the demand pool to cater to the market requirements. However, in real industry, engineers face issue with time, with regards to shortening the notification time when a mistake occurs, which is critical for decision making. Thus, in this review, researchers have tried to find a solution. Simulation can be employed to exploit a new concept of the solution to address complex data-based problem, and concentrate on the decision support system. This research tries to discern and diagnose the gap between the merging of both simulation as well as implementation of LM

From a Competition for Self-Driving Miniature Cars to a Standardized Experimental Platform: Concept, Models, Architecture, and Evaluation

Context: Competitions for self-driving cars facilitated the development and research in the domain of autonomous vehicles towards potential solutions for the future mobility. Objective: Miniature vehicles can bridge the gap between simulation-based evaluations of algorithms relying on simplified models, and those time-consuming vehicle tests on real-scale proving grounds. Method: This article combines findings from a systematic literature review, an in-depth analysis of results and technical concepts from contestants in a competition for self-driving miniature cars, and experiences of participating in the 2013 competition for self-driving cars. Results: A simulation-based development platform for real-scale vehicles has been adapted to support the development of a self-driving miniature car. Furthermore, a standardized platform was designed and realized to enable research and experiments in the context of future mobility solutions. Conclusion: A clear separation between algorithm conceptualization and validation in a model-based simulation environment enabled efficient and riskless experiments and validation. The design of a reusable, low-cost, and energy-efficient hardware architecture utilizing a standardized software/hardware interface enables experiments, which would otherwise require resources like a large real-scale test track.Comment: 17 pages, 19 figues, 2 table