Transmitter Positioning of Distributed Large-Scale Metrology Within Line-Less Mobile Assembly Systems

In Line-less Mobile Assembly Systems (LMAS) the mobilization of assembly resources and products enables rapid physical system reconfigurations to increase flexibility and adaptability. The clean-floor approach discards fixed anchor points, so that assembly resources such as mobile robots and automated guided vehicles transporting products can adapt to new product requirements and form new assembly processes without specific layout restrictions. An associated challenge is spatial referencing between mobile resources and product tolerances. Due to the missing fixed points, there is a need for more positioning data to locate and navigate assembly resources. Distributed large-scale metrology systems offer the capability to cover a wide shop floor area and obtain positioning data from several resources simultaneously with uncertainties in the submillimeter range. The positioning of transmitter units of these systems becomes a demanding task taking visibility during dynamic processes and configuration-dependent measurement uncertainty into account. This paper presents a novel approach to optimize the position configuration of distributed large-scale metrology systems by minimizing the measurement uncertainty for dynamic assembly processes. For this purpose, a particle-swarm-optimization algorithm has been implemented. The results show that the algorithm is capable of determining suitable transmitter positions by finding global optima in the assembly station search space verified by applying brute-force method in simulation.

Experimental and Numerical Study of Heat Pipe Heat Exchanger with Individually Finned Heat Pipes

The present study is devoted to the modeling, design, and experimental study of a heat pipe heat exchanger utilized as a recuperator in small air conditioning systems (airflow ≈ 300–500 m3/h), comprised of individually finned heat pipes. A thermal heat pipe heat exchanger model was developed, based on available correlations. Based on the previous experimental works of authors, refrigerant R404A was recognized as the best working fluid with a 20% heat pipe filling ratio. An engineering analysis of parametric calculations performed with the aid of the computational model concluded 20 rows of finned heat pipes in the staggered arrangement as a guarantee of stable heat exchanger effectiveness ≈ 60%. The optimization of the overall cost function by the “brute-force” method has backed up the choice of the best heat exchanger parameters. The 0.05 m traversal (finned pipes in contact with each other) and 0.062 m longitudinal distance were optimized to maximize effectiveness (up to 66%) and minimize pressure drop (less than 150 Pa). The designed heat exchanger was constructed and tested on the experimental rig. The experimental data yielded a good level of agreement with the model—relative difference within 10%.

Global optimization of default phases for parallel transmit coils for ultra-high-field cardiac MRI

The development of novel multiple-element transmit-receive arrays is an essential factor for improving B1+ field homogeneity in cardiac MRI at ultra-high magnetic field strength (B0 > = 7.0T). One of the key steps in the design and fine-tuning of such arrays during the development process is finding the default driving phases for individual coil elements providing the best possible homogeneity of the combined B1+-field that is achievable without (or before) subject-specific B1+-adjustment in the scanner. This task is often solved by time-consuming (brute-force) or by limited efficiency optimization methods. In this work, we propose a robust technique to find phase vectors providing optimization of the B1-homogeneity in the default setup of multiple-element transceiver arrays. The key point of the described method is the pre-selection of starting vectors for the iterative solver-based search to maximize the probability of finding a global extremum for a cost function optimizing the homogeneity of a shaped B1+-field. This strategy allows for (i) drastic reduction of the computation time in comparison to a brute-force method and (ii) finding phase vectors providing a combined B1+-field with homogeneity characteristics superior to the one provided by the random-multi-start optimization approach. The method was efficiently used for optimizing the default phase settings in the in-house-built 8Tx/16Rx arrays designed for cMRI in pigs at 7T.

Developing an Android-Based City Tour App using Evolutionary Algorithm

Traveling around a city and making transit in certain areas is called a city tour. Furthermore, determining the optimal city tour route can be considered as a traveling salesman problem. There are many kinds of algorithms to solve this, one of which is the Genetic Algorithm (GA). In developing the City Tour application, a platform is needed to be taken to various places anywhere and anytime. Finally, we developed an application that runs on mobile devices. This application is built on the Android platform so that its use can be more efficient. Furthermore, it can be concluded that the GA applied to the Android-based City Tour Application is reliable to determine city tour routes; this is evidenced by comparing GA with the brute force method, where GA provides optimum results with less running time.

Software-in-the-Loop Combined Machine Learning for Dynamic Responses Analysis of Floating Offshore Wind Turbines

Artificial intelligence (AI) brings a new solution to overcome the challenges of Floating offshore wind turbines (FOWTs) to better predict the dynamic responses with intelligent strategies. A new AI-based software-in-the-loop method, named SADA is introduced in this paper for the prediction of dynamic responses of FOWTs, which is proposed based on an in-house programme DARwind. DARwind is a coupled aero-hydro-servo-elastic in-house program for FOWTs, and a reinforcement learning method with exhaust algorithm and deep deterministic policy gradient (DDPG) are embedded in DARwind as an AI module. Firstly, the methodology is introduced with the selection of Key Disciplinary Parameters (KDPs). Secondly, Brute-force Method and DDPG algorithms are adopted to changes the KDPs’ values according to the feedback of 6DOF motions of Hywind Spar-type platform through comparing the DARwind simulation results and those of basin experimental data. Therefore, many other dynamic responses that cannot be measured in basin experiment can be predicted in good accuracy with SADA method. Finally, the case study of SADA method was conducted and the results demonstrated that the mean values of the platform’s motions can be predicted with higher accuracy. This proposed SADA method takes advantage of numerical-experimental method, basin experimental data and the machine learning technology, which brings a new and promising solution for overcoming the handicap impeding direct use of conventional basin experimental way to analyze FOWT’s dynamic responses during the design phase.

Automatic Makers as a Source for Olympiad Tasks

Automatic maker is meant as a device to produce (or compose) things by itself, by a model, customization or a program. Nowadays the most advanced automatic makers in mass use are 3D-printers.The purpose of the paper is to present methods of generating various Olympiad tasks by using evident images of virtual automatic makers. As a perspective, production (performing) of processes is also considered (as automatic 4D-makers). Besides of the main operation: putting a pixel (voxel), the following primitives with virtual things can be involved: cutting; gluing; putting a building block; erasing a building block; copying a fragment, (for 4D-) shifting a building block. Tasks are generated naturally: to make a given thing (perform a given simple process) optimally in any sense (with respect to time; to number of primitives; to number of building blocks etc.). Such tasks are well-understood, have short formulations and are difficult to be solved even with initial data of small volume; a “brute force” method is either inapplicable or gives too overestimate of complexity.

Deep energy retrofits: Toronto's urban single family housing stock.

There is a need to address the energy consumption of existing single family homes in the City of Toronto. This study outlines a process for developing and analyzing retrofit strategies for specific housing archetypes. The process was applied to Century, Century-Semi, and War Time Home archetypes. Housing data was collected and baseline energy models were prepared utilizing EnergyPlus software. Retrofit strategies were selected and analyzed for hygrothermal performance and cost. The process utilized a Brute Force method for retrofit selection considering the cost/benefit of each strategy and showed where in the process it was beneficial to upgrade each parameter. Furnace and air sealing parameters were typically upgraded early in the process as they showed an attractive cost/benefit. Basement walls and slab parameters were then upgraded, followed by exterior walls and roofs. Windows tended to be upgraded late in the process as they exhibited high capital costs compared to energy savings.

Deep energy retrofits: Toronto's urban single family housing stock.

There is a need to address the energy consumption of existing single family homes in the City of Toronto. This study outlines a process for developing and analyzing retrofit strategies for specific housing archetypes. The process was applied to Century, Century-Semi, and War Time Home archetypes. Housing data was collected and baseline energy models were prepared utilizing EnergyPlus software. Retrofit strategies were selected and analyzed for hygrothermal performance and cost. The process utilized a Brute Force method for retrofit selection considering the cost/benefit of each strategy and showed where in the process it was beneficial to upgrade each parameter. Furnace and air sealing parameters were typically upgraded early in the process as they showed an attractive cost/benefit. Basement walls and slab parameters were then upgraded, followed by exterior walls and roofs. Windows tended to be upgraded late in the process as they exhibited high capital costs compared to energy savings.

Autonomous Elbow Controller for Differential Drive In-Pipe Robots

The inspection of legacy nuclear facilities to aid in decommissioning is a world wide issue. One of the challenges is the characterisation of pipe networks within them. This paper presents an autonomous control system for the navigation of these unknown pipe networks, specifically focusing on elbows. The controller utilises three low-cost feeler sensors to navigate the FURO II robot around 150 mm short elbows. The controller is shown to allow the robot to safely navigate around an elbow on all 39 attempts comparing that with the brute force method which only completed five of the nine attempts and damaging the robot. This shows the advantages of the proposed controller. A new metric (Impulse) is also proposed to compare the extra force applied to the robot over the time it is slipping in the elbow due to the errors in the drive unit speeds. Using this metric, the controller is shown to decrease the Impulse applied to the robot by 213.97 Ns when compared to the brute force method.

A comparison of methods for determining performance based employee deployment in production systems

Employee deployment is a crucial process in production systems. Based on qualification and individual performance of employees, deployment decisions can lead to ambiguous outcomes. This paper first reviews the state of the art and further compares two methods based on combinatorial analysis for employee deployment. Therefore, this paper emphasizes the costs and benefits of a Brute Force and an alternative Greedy method. When considering the qualification and individual performance of each employee, both algorithms provide working solutions. In direct comparison, the outcome of the alternative Greedy algorithm is more efficient in terms of calculation time whereas the Brute Force method provides the combination with the global optimum. This means calculation time as well as quality of outcome differ. The exponential growth of employee allocation possibilities depends on the amount of employees and leads to high calculation times, when using a Brute Force method. The comparison of both methods reveal that the proposed alternative Greedy algorithm reaches nearly as high outcomes as the Brute Force does, with significantly less calculation time. Furthermore, this paper offers an insight into the impact of deployment decisions within production systems.