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Assembly lines are one of the places where energy consumption is intensive in manufacturing enterprises. The use of robots in assembly lines not only increases productivity but also increases energy consumption and carbon emissions. The purpose of this paper is to minimize the cycle time and total energy consumption simultaneously in parallel robotic assembly lines (PRAL).

Due to the NP-hardness of the problem, A Pareto hybrid discrete firefly algorithm based on probability attraction (PHDFA-PA) is developed. The algorithm parameters are optimized using the Taguchi method. To evaluate the results of the algorithm, a multi-objective programming model and a restarted simulated annealing (RSA) algorithm are used.

According to the comparative study, the PHDFA-PA has a competitive performance with the RSA. Thus, it is possible to achieve a sustainable PRAL through the proposed method by addressing the cycle time and total energy consumption simultaneously.

To the best knowledge of the authors, this is the first study addressing energy consumption in PRAL. The proposed method for PRAL is efficient in solving the multi-objective balancing problem.

The Smarandache anti‐geometry is a non‐euclidean geometry that denies all Hilbert’s 20 axioms, each axiom being denied in many ways in the same space. In this paper, one finds an economics model to this geometry by making the following correlations: a point is the balance in a particular checking account, expressed in US currency (points are denoted by capital letters); a line is a person, who can be a human being (lines are denoted by lower case italics); and a plane is a US bank, affiliated to the FDIC (planes are denoted by lower case boldface letters).

The current studies on the clothing silhouette are very limited. The purpose of this paper is to propose an innovative framework to intelligently identify the womenswear silhouette with the latest computer technologies. To clearly define the womenswear silhouette, an accurate numerical definition is proposed.

The study first processes and segments the useful parts on the static catwalk image data files following existing graphic extraction approaches. Six basic alphabetical womenswear silhouette types are selected and numerically defined. Then, the proposed framework automatically classifies the six basic womenswear silhouettes considering the different slopes between three main clothing parts. Six clothing situations are discovered according to different designs and the detailed cases are systematically categorized. In addition, aspects influencing the judgment of the clothing silhouettes such as the skin, the background, the drastic change points are also considered. The proposed silhouette definition and identification framework is novel and proved accurate.

The proposed definition and identification framework of womenswear silhouettes have been proved a viable approach that is fully compatible with the current computer technologies. The validation study shows that the presented identification procedure has a desirable accuracy over 90 percent.

The proposed methodology develops brand new standards to numerically define and identify the womenswear silhouette, which was not available in the past. Besides, the measurement, the identification and the classification procedures are fully validated by the image data collected from 14 world famous brands over 11 consecutive seasons. It is shown that the proposed numerical framework of the womenswear silhouettes is a robust one, considering all of the observed design variabilities.

This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored areas with potential for study and recommends future courses of action.

Recognising the enormous potential of just‐in‐time (JIT) concepts for boosting productivity and quality, an increasing number of US and European firms consider adopting JIT concepts in manufacturing. However, the transfer of a manufacturing policy from traditional to JIT always requires radical structural changes in a production line design. One typical example of these changes is uniform assembly which does not allow high variability in the production schedules. Consequently, major hindrance to uniform assembly is a random fluctuation of task processing times in assembly line balancing. This article proposes a heuristic which takes into account stochastic task processing times and further develops a work assignment with the lowest expected total cost as well as an assignment with the highest work completion probability crucial for the success of JIT manufacturing.

The purpose of this paper is to improve the traditional bug algorithms for the navigation of mobile robots in unknown environments by considering the limitations in previous works such as generating long path, limited to static environments as well as ignoring implementation issues. With this purpose, a new bug‐type algorithm termed Distance Histogram Bug (DH‐Bug) is proposed for overcoming these limitations.

DH‐Bug redefines the traditional motion modes and switching criteria to shorten the path length. In order to extend the framework of the traditional bug algorithms to tackle the navigation problem in dynamic environments, a new mode and the related switching conditions are designed for dealing with moving obstacles. Moreover, a realization method termed the Distance Histogram (DH) method which takes many implementation issues into full account is proposed for implementing DH‐Bug on real robots.

DH‐Bug is convergent in static environments and it also guarantees “approximate” convergence based on several reasonable assumptions when there are moving obstacles. Simulations results show that DH‐Bug generates shorter average path length than some classical Bug algorithms in static environments and it also performs well in most simulations that contain moving obstacles except for some extremely adverse scenarios which have been discussed in the paper. Experiments on real robots further verify its applicability in both static environments and dynamic environments containing moving obstacles.

Compared with previous works, DH‐Bug has three main contributions. First, in static environments, it can shorten the average path length than many classical bug algorithms in the premise of guaranteeing convergence. Second, it can be applied in dynamic environments containing moving obstacles. Third, unlike the previous bug algorithms that always ignore the practical implementation issues, DH‐Bug presents not only an abstract concept, but also a realization approach for realizing this concept on real robots.

There are times when the present state of an organisation cannot be fully appreciated without reference to the past. This is certainly true of Singapore International Airlines.

The purpose of this paper is to propose a new framework and improve a bi-directional people counting technique using an RGB-D camera to obtain accurate results with fast computation time. Therefore, it can be used in real-time applications.

First, image calibration is proposed to obtain the ratio and shift values between the depth and the RGB image. In the depth image, a person is detected as foreground by removing the background. Then, the region of interest (ROI) of the detected people is registered based on their location and mapped to an RGB image. Registered people are tracked in RGB images based on the channel and spatial reliability. Finally, people were counted when they crossed the line of interest (LOI) and their displacement distance was more than 2 m.

It was found that the proposed people counting method achieves high accuracy with fast computation time to be used in PCs and embedded systems. The precision rate is 99% with a computation time of 35 frames per second (fps) using a PC and 18 fps using the NVIDIA Jetson TX2.

The precision rate is 99% with a computation time of 35 frames per second (fps) using a PC and 18 fps using the NVIDIA Jetson TX2.

The proposed method can count the number of people entering and exiting a room at the same time. If the previous systems were limited to only one to two people in a frame, this system can count many people in a frame. In addition, this system can handle some problems in people counting, such as people who are blocked by others, people moving in another direction suddenly, and people who are standing still.

ESTABLISHING the right degree of diversification needed for a company's product lines can be a vexing task. In their eagerness to offer variety and selectivity to the customer, sales people tend to push for an ever increasing variety of models, designs, styles, patterns, colours and sizes. In contrast cost conscious production people may view this proliferation with misgivings. They realize only too well the tremendous toll—in terms of additional set‐up times, scheduling problems, training tasks and other expenses—that can result from needless diversity.