A new memetic algorithm for mitigating tandem automated guided vehicle system partitioning problem

Abstract Automated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in order reduces travel time and controls conflicts and congestions. This paper presents the development process of a new Memetic Algorithm (MA) for optimizing partitioning problem of tandem AGVS. MAs employ a Genetic Algorithm (GA), as a global search, and apply a local search to bring the solutions to a local optimum point. A new Tabu Search (TS) has been developed and combined with a GA to refine the newly generated individuals by GA. The aim of the proposed algorithm is to minimize the maximum workload of the system. After all, the performance of the proposed algorithm is evaluated using Matlab. This study also compared the objective function of the proposed MA with GA. The results showed that the TS, as a local search, significantly improves the objective function of the GA for different system sizes with large and small numbers of zone by 1.26 in average

Phased array ultrasonic testing of ‎offshore wind bolted flange ‎connections

Offshore wind will play a key role in the majority of countries' plans to accelerate towards NetZero ‎‎‎and low-carbon energy transitions. Using fasteners (bolts and nuts) as a joining strategy is a ‎‎common ‎practice in various sections of the Offshore Wind Turbines (OWT) which needs regular ‎‎Non-‎Destructive Testing (NDT). For example, the bolted connection between the monopile and the ‎‎‎transition piece is under an immense stress concentration, which can result in loosening and even ‎‎‎failure of the connection. The current procedure to test the bolts involves fixed permanent strain ‎‎‎gauges and/or ultrasonic methods (using single-element transducers) to ensure the specific preload is ‎maintained during the wind turbine operation. In the case of using the strain gauge, the ‎‎challenge is the ‎number of bolts used in turbines in a wind farm, which can result in thousands of ‎‎required strain ‎gauges, and then as a usual practice, only a very limited number of bolts can only be ‎‎monitored.‎ The ultrasonic stress measurement technology is based on the acoustoelasticity theory, the relationship ‎between ‎the acoustic wave velocity and material stress, and the change in the ultrasonic Time of Flight ‎‎(ToF) corresponded ‎to the change in the length of the bolt due to the tightening axial force. This ‎process will then rely on the ‎calibration procedure including measurement of the acoustoelastic ‎coefficient and also the ToF in the free-stress ‎bolt. In the traditional ultrasonic method, the operator ‎uses single-element transducers and assumes ‎any difference between the ToF of a bolt in service and ‎the calibration bolt corresponds to the stress (pre-load) ‎change. While this assumption can be true for a ‎brand-new bolt, similar to what is used in the lab for calibration, it ‎will ignore corrosion, defects, ‎ageing, creep, strain-hardening, fatigue and other material changes during the ‎service life. In this paper, ‎the Phased Array Ultrasonic Testing (PAUT) system will be used instead of the single-element ‎approach. The ‎‎advantage of the PAUT system over the single-element transducer is the possibility of ‎‎(I) ‎defect detection and (II) ‎stress measurement, simultaneously. Combining the defect detection and ‎stress measurement is critical, ‎otherwise, the ultrasonic stress measurement and calibration procedure ‎will be influenced by the possible defects. ‎Using the PAUT and an array instead of a single-element ‎transducer, will allow the detection of the possible ‎defects in some of the specific acoustic paths used ‎for the ToF measurement and then use alternative acoustic ‎paths for the stress measurement. ‎Furthermore, advanced post-processing algorithms like Total Focusing Method ‎‎(TFM) can allow the ‎possibility of focusing ‎on more threads which are usually critical points of concern in the ‎safety-‎critical bolts.‎ It should also be noted that the bolt material used for offshore applications is usually ‎marine-grade high-alloy steel and/or stainless steel which can result in a poor Signal-to-Noise Ratio ‎‎(SNR) corresponding to the austenitic microstructure and large grain noise. In this paper, Phase ‎Coherence Imaging (PCI) was used to improve the SNR value in the PAUT bolt testing. PCI is an ‎amplitude-free synthetic beamforming method, ‎which considers the phase dispersion at each discrete ‎image point. This allows‎ incoherent noises ‎resulting from side lobes, grating lobes, reverberations and ‎grain noise to be reduced.‎ The experimental setup included an M20 bolt tested by a 10 MHz 32-element array (Olympus, ‎USA) ‎and FIToolbox phased array controller (Diagnostic Sonar, UK). A washer-shaped load cell ‎‎(BoltSafe, ‎Netherlands) was used to verify the ultrasonic stress measurement results. The PAUT stress ‎measurement system could successfully detect the ToF variations caused by the bolt’s stress change ‎recorded by the load cell. For defect ‎detection, two Side-Drilled Holes (SDH) were produced between ‎the threads to quantify the scanning image and SNR. The Full Matrix Capturing (FMC) was then ‎imported into a Matlab-programmed TFM and PCI code. The application of these advanced post-‎processing algorithms resulted in a clearer scanning image, improved SNR value and detection of the ‎SDHs with a lower gain.

Memetic Algorithms for Business Analytics and Data Science: A Brief Survey

This chapter reviews applications of Memetic Algorithms in the areas of business analytics and data science. This approach originates from the need to address optimization problems that involve combinatorial search processes. Some of these problems were from the area of operations research, management science, artificial intelligence and machine learning. The methodology has developed considerably since its beginnings and now is being applied to a large number of problem domains. This work gives a historical timeline of events to explain the current developments and, as a survey, gives emphasis to the large number of applications in business and consumer analytics that were published between January 2014 and May 2018