A Multi-Object Genetic Algorithm for the Assembly Line Balance Optimization in Garment Flexible Job Shop Scheduling

Numerous clothing enterprises in the market have a relatively low efficiency of assembly line planning due to insufficient optimization of bottleneck stations.As a result,the production efficiency of the enterprise is not high,and the production organization is not up to expectations.Aiming at the problem of flexible process route planning in garment workshops,a multi-object genetic algorithm is proposed to solve the assembly line bal-ance optimization problem and minimize the machine adjustment path.The encoding method adopts the object-oriented path representation method,and the initial population is generated by random topology sorting based on an in-degree selection mechanism.The multi-object genetic algorithm improves the mutation and crossover operations according to the characteristics of the clothing process to avoid the generation of invalid offspring.In the iterative process,the bottleneck station is optimized by reasonable process splitting,and process allocation conforms to the strict limit of the station on the number of machines in order to improve the compilation efficiency.The effectiveness and feasibility of the multi-object genetic algorithm are proven by the analysis of clothing cases.Compared with the artificial allocation process,the compilation efficiency of MOGA is increased by more than 15%and completes the optimization of the minimum machine adjustment path.The results are in line with the expected optimization effect.

Dynamic Balance Control Based on an Adaptive Gain-scheduled Backstepping Scheme for Power-line Inspection Robots

This paper presents an adaptive gain-scheduled backstepping control(AGSBC) scheme for the balance control of an underactuated mechanical power-line inspection(PLI) robotic system with two degrees of freedom and a single control input.First, a nonlinear dynamic model of the balance adjustment process of the PLI robot is constructed, and then the model is linearized at a nominal equilibrium point to overcome the computational infeasibility of the conventional backstepping technique. Second, to solve generalized stabilization control issue for underactuated systems with multiple equilibrium points,an equilibrium manifold linearized model is developed using a scheduling variable, and then a gain-scheduled backstepping control(GSBC) scheme for expanding the operational area of the controlled system is constructed. Finally, an adaptive mechanism is proposed to counteract the impact of external disturbances. The robust stability of the closed-loop system is ensured by Lyapunov theorem. Simulation results demonstrate the effectiveness and high performance of the proposed scheme compared with other control schemes.

Reconstructed annual glacier surface mass balance in theányêmaqên Mountains,Yellow River source,based on snow line altitude

Annual mass balance is an important factor that reflects glacier change and glacier meltwater resources.In this study,we analyzed the changes in glacier area,snow line altitude(SLA)and surface elevation in theányêmaqên Mountain region using multisource remote sensing data.Then,the annual mass balance of two glaciers was reconstructed by using SLA-mass-balance gradient method.The results showed that the glacier area in theányêmaqên Mountains decreased by 29.4 km2from 1985 to 2017.The average SLAs of the Halong Glacier and Yehelong Glacier were approximately 5290 m and 5188 m,respectively.The glacier mass balance for the two glaciers from 1990 to 2020 was-0.71 m w.e.a^(-1) and-0.63 m w.e.a^(-1),respectively.Our results indicate that SLA is an important indicator of glacier changes,and a long sequence of SLAs can more accurately reconstruct the glacier mass balance of the glacier.The mean annual glacial meltwater-fed streamflow is 1.45×10^(7)m^(3) and 1.12×10^(7)m^(3),respectively.Sensitivity analysis indicates that summer air temperature plays a leading role in regard to the influential climatic factors of glacial retreat in theányêmaqên Mountains.This highlights the potential of the methodology for application on reconstructing annual glacier surface mass balance at larger scales without direct measurements.

Digital simulation studies on long transmission line protection based on balance of energy

The protection based balance of energy is a new technique specially proposed for long transmission lines. This technique depends upon the calculation of net energy into the transmission line by two independent methods and comparing them to indicate healthy and faulty conditions. In order to study the performance and feasibility of the protection based on balance of energy, the new protection has been extensively tested by using EMTP on a long transmission line with various configurations and operating conditions (including single pole line, double circuit lines and two phase operation). The results calculated by EMTP show that under any condition of a power system, the proposed technique has excellent performance,the viability even for high resistance ground faults and a short operation time.

High-gain planar TEM horn antenna fed by balanced microstrip line

A printed TEM horn antenna with high gain fed by balanced microstrip line is proposed. The radiation part of the antenna consists of two symmetrical triangular metal slice branches printed on the FR-4 substrate with 15 mm thickness. The two branches are fed by balanced microstrip line. The antenna is simulated by software CST MICROWAVE STUDIO and the equivalent adopted dipole model is proposed to describe the radiation characteristic of the antenna. The simulation results indicate that the frequency range is from 164 GHz to 5 GHz with reflection coefficient less than -6 dB, and the typical gain value is 8 dB in the operating bandwidth. In order to improve antenna gain without influencing the bandwidth, the length of the dielectric slab should be extended appropriately in the main radiation direction. By extending the length of the dielectric slab appropriately in the main radiation direction, the antenna gain can be improved significantly without the influence on the bandwidth. Besides, a metal disc loaded in the radiation direction makes the gain in band be more stable. The prototype has been fabricated and measured in microwave anechoic chamber which is coincident with the simulation results. This antenna can be widely applied in the UWB field.

Effective Hybrid Teaching-learning-based Optimization Algorithm for Balancing Two-sided Assembly Lines with Multiple Constraints

Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints （TALB-MC）. Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization （TLBO） algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search （VNS） is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm （LAHC） for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS.

MASS BALANCE SENSITIVITY TO CLIMATE CHANGE: A CASE STUDY OF GLACIER NO. 1 AT URUMQI RIVERHEAD, TIANSHAN MOUNTAINS, CHINA

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The processes and characteristics of mass balance on the Urumqi Glacier No. 1 during 1958-2009

As a solid reservoir, a glacier can regulate regional water resources. The annual net mass balance directly reflects the fluctuation of the glacier and climate variability. Based on 51 years of mass balance observation data, the mass balance of Tianshan Mountains Urumqi Glacier No. 1 experienced a nine times positive balance fluctuation and nine times negative balance fluctuation. There were 35 and 16 negative and positive balance years, respectively. From 1996/97 to 2008/09, 12 consecutive negative balance years were observed at Tianshan Mountains Urumqi Glacier No. 1. These results demon- strate that the Urumqi Glacier No. 1 is experiencing a strong negative balance, and the strongest negative balance, -931 mm w.e. （mm water equivalent）, during the observation period occurred in 2008. In addition, the cumulative mass balance reached 13,709 mm w.e. in 2008. However, in 2009, the mass balance was positive at 63 mm w.e. The equilibrium-line al- titude changes with the fluctuation in the mass balance, and the effective mass balance gradient is 7.4 mrn/m. In this paper, the headwaters of the Urumqi River were analyzed using meteorological data from 1958 to 2009, including the average seasonal temperature and precipitation. The results showed that the main factor associated with the mass balance variation of Glacier No. 1 is the fluctuation in the summer air temperature, followed by changes in the precipitation.

Optimization of Line Configuration and Balancing for Flexible Machining Lines

Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.

An efficient migrating birds optimization algorithm with idle time reduction for Type-I multi-manned assembly line balancing problem

Multi-manned assembly line,which is broadly utilized to assemble high volume products such as automobiles and trucks,allows a group of workers to assemble different tasks simultaneously in a multi-manned workstation.This additional characteristic of parallel operators increases the complexity of the traditional NP-hard assembly line balancing problem.Hence,this paper formulates the Type-I multi-manned assembly line balancing problem to minimize the total number of workstations and operators,and develops an efficient migrating birds optimization algorithm embedded into an idle time reduction method.In this algorithm,a new decoding mechanism is proposed which reduces the sequence-dependent idle time by some task assignment rules;three effective neighborhoods are developed to make refinement of existing solutions in the bird improvement phases;and temperature acceptance and competitive mechanism are employed to avoid being trapped in the local optimum.Comparison experiments suggest that the new decoding and improvements are effective and the proposed algorithm outperforms the compared algorithms.

Optimization of assembly line balancing using genetic algorithm

In a manufacturing industry, mixed model assembly line(MMAL) is preferred in order to meet the variety in product demand. MMAL balancing helps in assembling products with similar characteristics in a random fashion. The objective of this work aims in reducing the number of workstations, work load index between stations and within each station. As manual contribution of workers in final assembly line is more, ergonomics is taken as an additional objective function. Ergonomic risk level of a workstation is evaluated using a parameter called accumulated risk posture(ARP), which is calculated using rapid upper limb assessment(RULA) check sheet. This work is based on the case study of an MMAL problem in Rane(Madras) Ltd.(India), in which a problem based genetic algorithm(GA) has been proposed to minimize the mentioned objectives. The working of the genetic operators such as selection, crossover and mutation has been modified with respect to the addressed MMAL problem. The results show that there is a significant impact over productivity and the process time of the final assembled product, i.e., the rate of production is increased by 39.5% and the assembly time for one particular model is reduced to 13 min from existing 18 min. Also, the space required using the proposed assembly line is only 200 m2 against existing 350 m2. Further, the algorithm helps in reducing workers fatigue(i.e., ergonomic friendly).

Genetic Algorithm for Concurrent Balancing of Mixed-Model Assembly Lines with Original Task Times of Models

The growing global competition compels manufacturing organizations to engage themselves in all productivity improvement activities. In this direction, the consideration of mixed-model assembly line balancing problem and implementing in industries plays a major role in improving organizational productivity. In this paper, the mixed model assembly line balancing problem with deterministic task times is considered. The authors made an attempt to develop a genetic algorithm for realistic design of the mixed-model assembly line balancing problem. The design is made using the originnal task times of the models, which is a realistic approach. Then, it is compared with the generally perceived design of the mixed-model assembly line balancing problem.

A Heuristic Method for Two-sided Assembly Line Balancing Problem

A two-sided assembly line is typically found in plants producing large-sized products. Its advantages over a one-sided line and the difficulties faced in two-sided line balancing problems were discussed. A mathematical model for two-ALB problem was suggested. A modification of the “ranked positional weight” method, namely two-ALB RPW for two-ALB problems was developed. Experiments were carried out to verify the performance of the proposed method and the results show that it is effective in solving two-sided assembly line balancing problems.

An investigation on changes in glacier mass balance and hypsometry for a small mountainous glacier in the northeastern Tibetan Plateau

Mass balance is a key indicator of the sensitivity of glaciers to climate change. Field measurement is one of the most important ways to study the mass balance of glaciers. Based on observations of mass balance in the ablation zone of Shuiguan Glacier No.4, Qilian Mountains, China, combined with the balance ratio between accumulation and ablation, we established a linear relation between mass balance and altitude. The results show that the mean annual mass balance of this glacier was ~510 mm w.e. from 2010 to 2013. The uncertainty in the balance ratio value does not lead to a significant difference in the mass balance. The equilibrium-line altitude rose by 180 m from 1972 to 2013, while the accumulation–area ratio decreased from 0.68 to 0.25. These variations may be caused by changes in air temperature. Meanwhile, the glacier is at present not in a steady state, and it may continue to shrink by a further ~900 m, even without further climate warming. In the western Lenglongling Mountains, assuming that the glaciers are in a steady state and the Equilibrium-line altitudes(ELAs)remain similar, there will be only 46 glaciers left, covering a total area of 19.2 km^2, in other words, only 22.3% of the glaciers area in 1972.

MODEL OF OPERATING AND BALANCING ASSEMBLY LINE IN A MASS CUSTOMIZATION ENVIRONMENT

The successful implementation of mass customization lies on reengineeringtechnology and management methods to organize the production. Especially in assembly phase, variousproduct configurations, due-time penalties and order-driven strategy challenge the traditionaloperation and management of assembly lines. The business features and the operation pattern ofassembly line based on mass customization are analyzed. And the research emphatically studiesvarious technologic factors to improve customer satisfaction and their corresponding implementmethods in operating assembly line. In addition, the models are proposed for operating assembly lineunder dynamic process environment in mass customization. A genetic approach is developed to providethe optimal solution to the models. The effectiveness of the proposed approach is evaluated with anindustrial application.

Assembly Line Balancing Based on Double Chromosome Genetic Algorithm

Aiming at assembly line balancing problem,a double chromosome genetic algorithm(DCGA)is proposed to avoid trapping in local optimum,which is a disadvantage of standard genetic algorithm(SGA).In this algorithm,there are two chromosomes of each individual,and the better one,regarded as dominant chromosome,determines the fitness.Dominant chromosome keeps excellent gene segments to speed up the convergence,and recessive chromosome maintains population diversity to get better global search ability to avoid local optimal solution.When the amounts of chromosomes are equal,the population size of DCGA is half that of SGA,which significantly reduces evolutionary time.Finally,the effectiveness is verified by experiments.

Mixed-Model U-Shaped Assembly Line Balancing Problems with Coincidence Memetic Algorithm

Mixed-model U-shaped assembly line balancing problems (MMUALBP) is known to be NP-hard resulting in it being nearly impossible to obtain an optimal solution for practical problems with deterministic algorithms. This paper pre-sents a new evolutionary method called combinatorial optimisation with coincidence algorithm (COIN) being applied to Type I problems of MMUALBP in a just-in-time production system. Three objectives are simultaneously considered;minimum number workstations, minimum work relatedness, and minimum workload smoothness. The variances of COIN are also proposed, i.e. CNSGA II, and COIN-MA. COIN and its variances are tested against a well-known algo-rithm namely non-dominated sorting genetic algorithm II (NSGA II) and MNSGA II (a memetic version of NSGA II). Experimental results showed that COIN outperformed NSGA II. In addition, although COIN-MA uses a marginal CPU time than CNSGA II, its other performances are dominated.

Optimization of Energy Resource Management for Assembly Line Balancing Using Adaptive Current Search

This paper aimed to present the optimization of energy resource management in a car factory by the adaptive current search (ACS)—one of the most efficient metaheuristic optimization search techniques. Assembly lines of a specific car factory considered as a case study are balanced by the ACS to optimize their energy resource management. The workload variance of the line is performed as the objective function to be minimized in order to increase the productivity. In this work, the ACS is used to address the number of tasks assigned for each workstation, while the sequence of tasks is assigned by factory. Three real-world assembly line balancing (ALB) problems from a specific car factory are tested. Results obtained by the ACS are compared with those obtained by the genetic algorithm (GA), tabu search (TS) and current search (CS). As results, the ACS outperforms other algorithms. By using the ACS, the productivity can be increased and the energy consumption of the lines can be decreased significantly.

CONCURRENT PRODUCT PORTFOLIO PLANNING AND MIXED PRODUCT ASSEMBLY LINE BALANCING

Reconfigurable products and manufacturing systems have enabled manufacturers to provide ＂cost effective＂ variety to the market. In spite of these new technologies, the expense of manufacturing makes it infeasible to supply all the possible variants to the market for some industries. Therefore, the determination of the right number of product variantsto offer in the product portfolios becomes an important consideration. The product portfolio planning problem had been independently well studied from marketing and engineering perspectives. However, advantages can be gained from using a concurrent marketing and engineering approach. Concurrent product development strategies specifically for reconfigurable products and manufacturing systems can allow manufacturers to select best product portfolios from marketing, product design and manufacturing perspectives. A methodology for the concurrent design of a product portfolio and assembly system is presented. The objective of the concurrent product portfolio planning and assembly system design problem is to obtain the product variants that will make up the product portfolio such that oversupply of optional modules is minimized and the assembly line efficiency is maximized. Explicit design of the assembly system is obtained during the solution of the problem. It is assumed that the demand for optional modules and the assembly times for these modules are known a priori. A genetic algorithm is used in the solution of the problem. The basic premise of this methodology is that the selected product portfolio has a significant impact on the solution of the assembly line balancing problem. An example is used to validate this hypothesis. The example is then further developed to demonstrate how the methodology can be used to obtain the optimal product portfolio. This approach is intended for use by manufacturers during the early design stages of product family design.

Assembly Line Balancing Using Fuzzy Logic: A Case Study of a Tricycle Assembly Line

The application of fuzzy logic in balancing a single model tricycle assembly line is presented in this study. MATLAB simulation software was used in the analysis of the primary and secondary data obtained from the assembly line under study. Results obtained from the study show that the efficiency of the line increased from 88.1% to 92.4%. The total idle time was also reduced by 56.5%. This indicates an improvement in the efficiency of the line, reduction of bottleneck, and even distribution of tasks along the line for the company under study.