Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.

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.

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.

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.

Realization of embedded control module for micro assembly line

A modularized,network,reconfigurable architecture and design method of embedded control module is proposed.This control module uses a TMS320F2812 chip as the core,and introduces modularization,network,reconfigurable theory to the design of control module to better meet the flexible and reconfigurable control need of assembly line.The design method of the control module is verified by constructing a control experiment based on controlling of precision x-y displacement platform through a CAN bus.Experimental results show that the controlling repeat position accuracy of precision x-y platform by control module is 0.5μm and the position error is less than 1μm which meet the needs of micro-adjustment pose of assembly line.

Heuristics for Mixed Model Assembly Line Balancing Problem with Sequencing

The growing global competition compels organizations to use many productivity improvement techniques. In this direction, assembly line balancing helps an organization to design its assembly line such that its balancing efficiency is maximized. If the organization assembles more than one model in the same line, then the objective is to maximize the average balancing efficiency of the models of the mixed model assembly line balancing problem. Maximization of average balancing efficiency of the models along with minimization of makespan of sequencing models forms a multi-objective function. This is a realistic objective function which combines the balancing efficiency and makespan. This assembly line balancing problem with multi-objective comes under combinatorial category. Hence, development of meta-heuristic is inevitable. In this paper, an attempt has been made to develop three genetic algorithms for the mixed model assembly line balancing problem such that the average balancing efficiency of the model is maximized and the makespan of sequencing the models is minimized. Finally, these three algorithms and another algorithm in literature modified to solve the mixed-model assembly line balancing problem are compared in terms of the stated multi-objective function using a randomly generated set of problems through a complete factorial experiment.

Application Research of assembly line modeling based on Time Petri Net

With the continuous progress of manufacturing industry,automatic assembly line has become a very mature production mode in modern factories,and the quality of assembly line design has become an important issue related to the development of manufacturing enterprises.In this paper,a graphical model based on Petri Net is established for the first full load time of the assembly line.The accessibility of the P/T system and the production rhythm of the assembly line are calculated by computer simulation.Finally,according to the simulation model,an experimental platform is built to verify the rationality of the model.Experimental results show that the model can accurately express the equipment allocation process of assembly line.

Solving Level Scheduling in Mixed Model Assembly Line by Simulated Annealing Method

This paper presents an application of the simulated annealing algorithm to solve level schedules in mixed model assembly line. Solving production sequences with both number of setups and material usage rates to the minimum rate will optimize the level schedule. Miltenburg algorithm (1989) is first used to get seed sequence to optimize further. For this the utility time of the line and setup time requirement on each station is considered. This seed sequence is optimized by simulated annealing. This investigation helps to understand the importance of utility in the assembly line. Up to 15 product sequences are taken and constructed by using randomizing method and find the objective function value for this. For a sequence optimization, a meta-heuristic seems much more promising to guide the search into feasible regions of the solution space. Simulated annealing is a stochastic local search meta-heuristic, which bases the acceptance of a modified neighboring solution on a probabilistic scheme inspired by thermal processes for obtaining low-energy states in heat baths. Experimental results show that the simulated annealing approach is favorable and competitive compared to Miltenburg’s constructive algorithm for the problems set considered. It is proposed to found 16,985 solutions, the time taken for computation is 23.47 to 130.35, and the simulated annealing improves 49.33% than Miltenberg.

Intelligent sorting method for assembly line based on visual positioning and robotic arm model predictive control

The existing steering device in the fruit and vegetable packaging assembly line cannot adjust the attitude of lettuce to a unified attitude,affecting the input and packaging process of the packaging machine.This study proposes an intelligent assembly line sorting method based on the visual positioning and model predictive control of a robotic arm.First,lightweight improvement based on the YOLOv5 is realized,the lettuce stalk in the background of the conveyor belt is promptly identified,the image of the lettuce stalk in the anchor box area is processed,and the edge contour point set is determined to extract the pixel coordinates of the optimal grasp point and mirror inclination angle of the lettuce.For the intelligent assembly line system,a robot arm kinematics model is constructed and the robot kinematics inverse solutions are calculated.Additionally,the lettuce movement speeds are dynamically measured by the vision system.A combination of the model prediction control,dynamic tracking,and rapid sorting of the lettuce by the robot claw is realized.The results show that the average detection time of a single frame image in the visual positioning part is 0.014 s,which is reduced by 50%;the accuracy and recall are 98%and 95%,respectively.The detection time is significantly reduced by ensuring accuracy.Within the current speed range of the packaging assembly line conveyor belt,the manipulator can grasp lettuce at different speeds stably and fast;the average axial error,average radial error,and adjusted average inclination angle error are 0.71 cm,1.02 cm,and 3.79°,respectively,verifying the high efficiency and stability of the model.The proposed method of this study enables application in the intelligent sorting operation of industrial assembly lines.

A dynamic delivery strategy for material handling in mixed-model assembly lines using decentralized supermarkets

Material handling has become one of the major challenges in modern production management.Consequently,this paper intends to investigate the part delivery of mixedmodel assembly lines with decentralized supermarkets and tow trains.Besides,uncertain exception disturbances,including tow train failures and adjustments of the production sequence,are also considered.To solve this problem,a heuristic-based dynamic delivery strategy is proposed,which dynamically schedules the route,departure time,quantities and types of loaded parts for each tour.To evaluate the performance of this strategy,it is used to solve an instance in comparison with the periodic delivery strategy,experimental results are reported and their performances are compared under different metrics.Moreover,a multi-scenario analysis is employed to determinate the long-term decisions,including the number of tow trains and the route layout.Finally,the critical storage is suggested to be set for each station to avoid part starvation resulting from disturbances,and its effect on the delivery performance is investigated.

Just-in-time parts feeding optimization for assembly lines under travel time uncertainty

Just-in-time(JIT)part feeding is adopted by more and more automobile producers.Based on this part feeding policy,vehicles perform their assigned routes cyclically and provide stations with the exact quantity of parts required until the next arrival of the vehicle.However,if there are uncertain travel times,a shortage of materials in stations will be caused.In this paper,the JIT part feeding optimization problem under travel time uncertainty is studied.The uncertain travel time is represented by the interval number according to the actual situation.To minimize the largest possible vehicle trip time,the optimization model is developed based on robust optimization.In the model,a route-dependent uncertain parameter is introduced.Through this model,the route of each vehicle and the parts load needed to be delivered by the vehicle can be calculated.A hybrid simulated annealing algorithm is designed to solve this model.The parts feeding planning for an engine assembly line is taken as an example.By the Monte Carlo simulation,the relationship between the line stoppage probability and the uncertain parameter is studied to obtain the final solution.The effectiveness of the method is demonstrated by this case study.

New Accord rolling off assembly line

On Mar. 26, the first Accord sedan rolled off the production line in Guangzhou Honda Automobile Co. Ltd., a joint venture between Guangzhou Automobile Group and Honda Co. of Japan. With total registered investment of more than RMB 1.16 bill., both sides take equally 50%. The cooperative term will last

Assembly Unit Resource Balancing Strategy based on Discrete Production Mode

Aiming at the characteristics of obvious block division and strong discreteness in the assembly production mode of electronic products,this paper proposes a composite U-shaped flexible assembly line model,and establishes a multi-objective optimization mathematical model on this basis.According to the characteristics of the model,the improved ranked positional weight(RPW)method is used to adjust the generation process of the initial solution of the genetic algorithm,so that the genetic algorithm can be applied to the block task model.At the same time,the adaptive cross mutation factor is used on the premise that tasks between different blocks are not crossed during cross mutation,which effectively improves the probability of excellent individuals retaining.After that,the algorithm is used to iterate to obtain the optimal solution task assignment.Finally,the algorithm results are compared with actual production data,which verifies the validity and feasibility of the assembly line model for discrete production mode proposed in this paper.

The Coupled Operational Systems:A Linear Optimisation Review

The purpose of this review is to summarise the existing literature on the operational systems as to explain the current state of understanding on the coupled operational systems.The review only considers the linear optimisation of the operational systems.Traditionally,the operational systems are classified as decoupled,tightly coupled,and loosely coupled.Lately,the coupled operational systems were classified as systems of time-sensitive and time-insensitive operational cycle,systems employing one mix and different mixes of factors of production,and systems of single-linear,single-linear-fractional,and multi-linear objective.These new classifications extend the knowledge about the linear optimisation of the coupled operational systems and reveal new objective-improving models and new state-of-the-art methodologies never discussed before.Business areas affected by these extensions include product assembly lines,cooperative farming,gas/oil reservoir development,maintenance service throughout multiple facilities,construction via different locations,flights traffic control in aviation,game reserves,and tramp shipping in maritime cargo transport.

Decomposition Methods for Manufacturing System Scheduling:A Survey

Manufacturing is the application of labor, tools,machines, chemical and biological processing, to an original raw material by changing its physical and geometrical characteristics, in order to make finished products. Since the first industrial revolution, to accommodate the large-scale production,tremendous changes have happened to manufacturing through the innovations of technology, organization, management, transportation and communication. This work first reviews the highvolume low-mix process by focusing on the quantity production,transfer line and single model assembly line. Then, it reviews the high-volume high-mix process. For such a process type,mixed/multi model assembly line is usually adopted. Hence,two main decisions on them, i.e., balancing and, sequencing are reviewed. Thereafter, it discusses the low-volume high-mix process in detail. Then, technology gap and future work is discussed, and at last, conclusions are given.

Design and Structural Analysis of Flexible Wearable Chair Using Finite Element Method

The flexible wearable chair is like a light weight mobile exoskeleton that allows people to sit any-where in any working position. The traditional chair is difficult to move to different working locations due to its large size, heavy weight (~5 - 7 kg) and rigid structure and thus, they are inappropriate for workplaces where enough space is not available. Flexible wearable chair has a gross weight of 3 kg as it utilizes light-weight aluminium alloy members. Unlike the traditional chair, it consists of kinematic pairs which enable taking halts between continuous movements at any working position and thus, it is capable of reducing the risk of the physical musculoskeletal disorder substantially among workers. The objective of this paper is to focus on the mechanical design and finite element analysis (FEA) of the mechanism using ANSYS® software. In the present work, all the parts of the mechanism are designed under static load condition. The results of the analysis indicate that flexible wearable chair satisfies equilibrium and stability criterion and is capable of reducing fatigue during working in an assembly line/factory.

Technological Analysis on Motor Stall and Its Perspective

The brush lock is due to assembly tightly during assembling three gripper so that it curls after some time in motor and bare motors.The motor happen to have current decreasing and cause rotary too slowly is an important technique problem.At last the motor hasn’t worked due to disconnection.It give company to bring assembly issue for customers.So the motor stall is main issue in motor working.We shall pay more attention to it necessarily and shall be strict quality inspection and we shall monitor the flow line for the sake of decreasing it.We shall solve the problem as soon as possible and communicate with the customer engineers.Unloaded rotation is radical in the base inspection.The engineer need to negotiate with supplying engineers for the qualified material of brush.Increasing inspection into more times is a method to decrease unqualified brushes.Some experiment method is explained to analyze for customer engineers.Two kinds of motors ie.stepping and asynchronous motor and motors used in future in car is explained to further knowledge to motor’s application.Such as the experiment with torque,voice and electric voltage converter.The pseudo soldering results the slow rotary.The reverse voltage is a reason for a motor to slow rotary even stall.

Minimizing Products Rates Variation in Just-in-Time Mixed-Model Manufacturing

Mixed-Model assembly lines are often used in manufacturing based on just-in-time techniques. The effective utilization of these lines requires a schedule for assembling the different models be determined. The objective is to minimize the total deviation of actual production rates from the desired production rates. Mathematical method with the optimization algorithm is proposed here to solve this problem. To prove the efficiency of the proposed algorithm, a number of test problems are solved. The results show that the proposed algorithm is an efficient and effective algorithm which gives better results with the large problem sizes. This paper presents a practical procedure to minimize total product variation rates, and easy to use by practitioner.