International Journal of Research in Industrial Engineering
Volume:9 Issue: 2, Spring 2020

Nowadays, the control of the traffic in the urban roads and in the highway has been a big challenge as the number of increase in the auto mobiles. So to overcome this problem we use the detection and tracking the vehicles using the traffic surveillance system. We can manage and control the traffic more easily. It is very complicated and a challenging task to identify the vehicle or a moving object in a complex environment with various background. The ratio detected of such algorithms depends on the quality of the foreground mask generated. Therefore this project is to present the detection and tracking the vehicles and the pedestrians in an efficient method which focus on trajectory motion of the vehicles and the pedestrians. In this proposed method, the pixels in the background are preserved which can be cars, bikes, buses, pedestrian, etc., the rest is discarded as the noise. Hence, our proposed method detects the vehicles and the pedestrians as mentioned and discards the rest noise as well in the same time. Here the quality of the generated foreground mask is more to increase the detection ratio. The performance is compared with other standard methods qualitatively and quantitatively.

This project is a case study conducted in a manufacturing company aiming at improving its productivity using line balancing techniques. Waste reduction, especially the time waste, is an important factor to shrink the manufacturing cost. The main purpose of this project is to suggest a better line balancing approach with an aim of reducing the idle time, work station number, and manpower requirement while improving the efficiency to meet the target production in the apparel manufacturing organization. For accomplishing the purpose, different line balancing methods named Largest Candidate Rule, Kilbridge & Wester method, and Ranked Positional Weight method carried out for analyzing the line efficiency, production rate, work station number, manpower requirement, and time utilization. Finally, an efficient and balanced line were proposed with respect to the auspicious outcome of the production area. Also, by using the line balancing techniques, a new sequence of work has been developed to arrange the work elements into the workstation. Some optimum layout has been proposed that has minimized the idle time and manpower requirement.

This work presents Amplified Black Hole Algorithm (ABHA) for solving optimal reactive power problem. In the projected approach ABHA, Gravitational Search Algorithm (GSA) is merged with Black Hole Algorithm (BHA). Power loss reduction is the key objective in the proposed work. The gravitational force between stars and the progression of stars to the black hole is attuned while explore the solution space. Assumption made that heavy objects are stars in a gravitational system, which become black holes and the exploitation of GSA is enhanced. During the progression of the projected algorithm, the radius of the black hole diminishes and more objects are included, which assist to stop early convergence. To improve the exploration and exploitation, stars gravity information has been utilized. During the progression of the projected algorithm, the radius of the black hole diminishes, and more objects are included, which assist to stop early convergence. Some of the most excellent objects turn out to be the black hole, affect other objects by their sturdy gravity. The other objects are alienated into two groups: Heavy agents and light agents. Proposed ABHA has been tested in standard IEEE 14, 30, 57, 118, 300 bus test systems and simulation results show the projected algorithm reduced the real power loss comprehensively.

Amid the previous three decades, the topic of image processing has gained vital name and recognition among researchers because of their frequent look in varied and widespread applications within the field of various branches of science and engineering. As an example, image processing is helpful to issues in signature recognition, digital video processing, remote sensing and finance. Image processing models are used for detecting the face. The aim of this thesis is to solve the face-detection in the first attempt using the Haar-cascade classifier from images containing simple and complex backgrounds. It is one of the preeminent detectors in terms of reliability and speed. We introduced a new method to deal with the frontal face images by using a modified Haar cascade algorithm. By using this algorithm, we can detect the image as well as the coordinates. The main attraction of this paper is to solve different types of images having one object, two objects, and three objects which can’t be solved by any of the existing methods but can be solved by our proposed method.

The Quadratic Assignment Problem (QAP) is one of the problems of combinatorial optimization belonging to the NP-hard problems’ class and has a wide application in the placement of facilities. Thus far, many efforts have been made to solve this problem and countless algorithms have been developed to achieve the optimal solutions; one of which is the Simulated Annealing (SA) algorithm. This paper aims at finding a suitable layout for the facilities of an industrial workshop by using a Developed Simulated Annealing (DSA) method.

Decision-making models such as Analytical Hierarchy Process (AHP), Weighted Decision Matrix (WDM), Pugh Matrix and the likes have been able to assist in the decision process considering the objectives of each evaluation criteria in the alternatives. However, these models need to consider the qualitative and subjective nature of the design features. In order to reduce the unbalanced scale of judgment and the uncertainty associated with the crisp information in the decision process, fuzzified and hybridized models are necessary. Existing hybridized decision models applied for machine concept selection deploy several design features and sub-features at the conceptual product design, which thus make the decision making process to be tedious. In light of this, this article presents a hybridized decision-making model, which harness the comparative strength and computational integrity of fuzzy pairwise comparison matrix and fuzzy weighted average, to numerically analyse a reasonable amount of machine design features, thereby making decision making process less tedious. Design for reconfigurability and functionality which are peculiar to reconfigurable machines was introduced using a Reconfigurable Assembly Fixture (RAF) as a case study while other design features related to design concept evaluation were grouped under design for X. The result of the hybridized model shows that, concept three is the optimal design from four sets of designs. This is compared to previous publication using the RAF design concepts with different design features and sub-features. The comparison indicates that there is a close range in the final values of the designs due to the inclusion of several sub-features in the decision process which were not used in the previous study.

Many numbers of speed breakers were constructed on different outlets and even inside the city of Woldia for the purpose of reducing car accidents that occurred due to over speed driving. Surely while the speed of the vehicle is reduced or the driver drives the vehicle at low speeds, the probability of accident occurrence is very low. But reducing the speed in such a manner or using sudden breaking will result in kinetic energy wastage due to change in velocity and wastage of potential energy due to climbing of the beaker height. In this study, the number of vehicles that were passed on the specified speed breaker was recorded in seven days and wasted energy was calculated and analyzed for each type of vehicle for the seven days. A total amount of 376,849.6kJ is wasted during those days on a single speed breaker which has a huge impact on the economy of the country by increasing fuel consumption of individual cars.