Smart control of the assembly process with a fuzzy control system in the context of Industry 4.0

Assembly line balancing is important for the efficiency of the assembly process, however, a wide range of disruptions can break the current workload balance. Some researchers explored the task assignment plan for the assembly line balancing problem with the assumption that the assembly process is smooth with no disruption. Other researchers considered the impacts of disruptions, but they only explored the task re-assignment solutions for the assembly line re-balancing problem with the assumption that the re-balancing decision has been made already. There is limited literature exploring on-line adjustment solutions (layout adjustment and production rate adjustment) for an assembly line in a dynamic environment. This is because real-time monitoring of an assembly process was impossible in the past, and it is difficult to incorporate uncertainty factors into the balancing process because of the randomness and non-linearity of these factors. However, Industry 4.0 breaks the information barriers between different parts of an assembly line, since smart, connected products, which are enabled by advanced information and communication technology, can intelligently interact and communicate with each other and collect, process and produce information. Smart control of an assembly line becomes possible with the large amounts of real-time production data in the era of Industry 4.0, but there is little literature considering this new context. In this study, a fuzzy control system is developed to analyze the real-time information of an assembly line, with two types of fuzzy controllers in the fuzzy system. Type 1 fuzzy controller is used to determine whether the assembly line should be re-balanced to satisfy the demand, and type 2 fuzzy controller is used to adjust the production rate of each workstation in time to eliminate blockage and starvation, and increase the utilization of machines. Compared with three assembly lines without the proposed fuzzy control system, the assembly line with the fuzzy control system performs better, in terms of blockage ratio, starvation ratio and buffer level. Additionally, with the improvement of information transparency, the performance of an assembly line will be better. The research findings shed light on the smart control of the assembly process, and provide insights into the impacts of Industry 4.0 on assembly line balancing.     

Multi-objective fuzzy assembly line balancing using genetic algorithms

This paper presents a fuzzy extension of the simple assembly line balancing problem of type 2 (SALBP-2) with fuzzy job processing times since uncertainty, variability, and imprecision are often occurred in real-world production systems. The jobs processing times are formulated by triangular fuzzy membership functions. The total fuzzy cost function is formulated as the weighted-sum of two bi-criteria fuzzy objectives: (a) Minimizing the fuzzy cycle time and the fuzzy smoothness index of the workload of the line. (b) Minimizing the fuzzy cycle time of the line and the fuzzy balance delay time of the workstations. A new multi-objective genetic algorithm is applied to solve the problem whose performance is studied and discussed over known test problems taken from the open literature.     

A meta-heuristic algorithm for the fuzzy assembly line balancing type-E problem

Consideration is given to a single-model assembly line balancing problem with fuzzy task processing times. The problem referred to herein as f-SALBP-E consists of finding a combination of the number of workstations and the cycle time as well as a respective line balance such that the efficiency of the line is maximized. f-SALBP-E is an extension of the classical SALBP-E under fuzziness. First, a formulation of the problem is given with the tasks processing times presented by triangular fuzzy membership functions. Then, since the problem is known to be NP-hard, a meta-heuristic based on a Genetic Algorithm (GA) is developed for its solution. The performance of the proposed solution approach is studied and discussed over multiple benchmarks test problems taken from the open literature. The results demonstrate very satisfactory performance for the developed approach in terms of both solution time and quality.     

Modelling for flexible manufacturing systems and structural properties of optimal work routing policy

We consider flexible manufacturing systems (FMSs) which are composed of a set of workstations linked together with a material handling system (MHS). Each workstation consists of an input buffer, a single machine and an output buffer. The MHS consisting of a single cart routes work among the workstations according to the process paths required by the work. We deal with an optimal control problem in this FMS. We model the FMS as a closed queueing network. In the model, the cart routes the work to the workstations in accordance with a Markov routing with exponentially distributed routing time, and the machines process work with exponentially distributed processing time. An objective is to find a work routing policy that maximizes the total expected reward earned by operating machines. This optimal control problem is formulated as an undiscounted semi-Markov decision process. Structural properties of an optimal policy are analysed. Moreover, a sufficient condition is derived for the optimal policy to be of control limit type. An example is given to illustrate the result.     

基于PLC的一体化压力铸造控制系统

通过对设备主体、现场控制系统、高性能数字组合阀及控制软件等核心模块的设计,开发集低压铸造、差压铸造、调压铸造多项功能于一体的反重力铸造系统。在设备运行过程中,采用模糊自整定PID算法对生产过程进行控制。利用上位机软件可方便地实现对一体化压力铸造系统的自动化控制,并能够实时显示参数和图形化显示铸造过程。实验表明,该系统可提高铸造系统的自动化程度和铸件的精度,功能多样且实用性强,实现了铸造系统的自动化工作过程。     

Soft computing framework for intelligent human–machine system design,simulation and optimization

 This paper proposes a novel soft-computing framework for human–machine system design and simulation based on the hybrid intelligent system techniques. The complex human–machine system is described by human and machine parameters within a comprehensive model. Based on this model, procedures and algorithms for human–machine system design, economical/ergonomic evaluation, and optimization are discussed in an integrated CAD and soft-computing framework. With a combination of individual neural and fuzzy techniques, the neuro-fuzzy hybrid soft-computing scheme implements a fuzzy if-then rules block for human–machine system design, evaluation and optimization by a trainable neural fuzzy network architecture. For training and test purposes, assembly tasks are simulated and carried out on a self-built multi-adjustable laboratory workstation with a flexible motion measurement and analysis system. The trained neural fuzzy network system is able to predict the operator's postures and joint angles of motion associated with a range of workstation configurations. It can also be used for design/layout and adjustment of human assembly workstations. The developed system provides a unified, intelligent computational framework for human–machine system design and simulation. Case studies for workstation system design and simulation are provided to illustrate and validate the developed system.     

Dynamic routing in reentrant flexible manufacturing systems

Consider a flexible manufacturing system (FMS), with several parallel production lines. Each line is statistically balanced. Due to process time and yield variations, some workstations may be temporarily starved of parts during the FMS operation, while others may have too many. The purpose of the dynamic routing algorithm described here is to achieve real-time load balancing in a stochastic processing environment and thus to increase the performance of the system in throughput, workload balance and reduced work-in-process queues. We formulate the problem and develop an optimal stationary policy (for two lines that have a material handling transport between them) based on the input buffer state of each station.     

宽板厂精整线改造自动化系统设计

论述了基于Tmeic V3000的某宽板厂精整线改造的自动化系统。介绍了精整线的工艺流程,讨论了自动化系统的硬件和软件,分析了仿真控制和设备控制。该自动化系统先进、可靠、经济,满足了企业现代化生产的要求。     

Design of assembly lines with the concurrent consideration of productivity and upper extremity musculoskeletal disorders using linear models

Work-related musculoskeletal disorders (WMSDs) are common occupational diseases among assembly workers due to repetitive motions or heavy workloads. The conventional approaches to decreasing WMSDs in assembly workers usually focus on individual assembly work at the station level. These approaches, however, do not pay enough attention to work allocation at the whole assembly line level such as balancing ergonomic burdens among workers by proper work assignment. This paper presents a methodology that can be used to integrate ergonomic measures of upper extremities into assembly line design problems. Linear models are developed to link work-worker assignment to the upper extremity ergonomic measures based on a guideline from American Conference of Governmental Industrial Hygienists. These linear models allow ergonomic and productivity measures to be integrated as a mixed-integer programming model. The case studies of this paper show the new model can effectively balance and control exposure levels in the upper extremity while not significantly decreasing line efficiency. This research shows the potential to reduce the need of numerous task adjustments for ergonomic improvement after initial assembly line design in conventional trial-and-error based assembly task adjustment. Furthermore, these linearization methods can be generalized in order to incorporate other ergonomic measures in tabulated forms into assembly line design problems.     

Intelligent design and planning of manual assembly workstations: A neuro-fuzzy approach

The design of manual assembly workstations, as with most forms of designs, is highly iterative and interactive. The designer has to consider countless constraints and solutions for contradictory goals. In order to assist the designer in design process, it is required to develop a new intelligent methodology and system. This paper develops a neuro-fuzzy hybrid approach to intelligent design and planning of manual assembly workstations. Problems, related to workstation layout design, planning, and evaluation, are discussed in detail. A fuzzy neural network is used to predict the ranges of anatomical joint motions and to design or adjust workstations and tasks. The neuro-fuzzy computing scheme is integrated with operator's posture analysis and evaluation. For training and test purposes, experiment is carried out to simulate assembly tasks on a multi-adjustable assembly workstation equipped with a flexible PEAK motion measurement and analysis system. The trained neural network is capable of memorizing and predicting the joint angles associated with a range of workstation configurations. Thus, it can also be used for the design/layout and on-line adjustment of manual assembly workstations. Thus, the developed system provides a unified, computational intelligent framework for the design, planning and simulation of manual assembly workstations.     

煤矿自动化发展趋势

分析了煤矿自动化发展过程,即从单机自动化、综合自动化、矿山物联网到矿山信息物理系统CPS,指出煤矿自动化是一个逐步实现信息系统与矿山物理系统相融合的过程,单机自动化、综合自动化、矿山物联网和矿山CPS只是这个过程中不同时期所表现出来的特征;分析了综合自动化、矿山物联网在煤矿实际应用中存在的问题,即综合自动化和矿山物联网均未考虑信息与事件的置信度、未采用发布与订阅机制、未考虑物理世界的不确定因素、未将人及其行为作为煤矿自动化系统中的要素来考虑,指出要使信息系统与矿山物理系统融合得更加紧密,矿山CPS是煤矿自动化发展的必然趋势。     

CPS技术在柔性滑板生产线中的运用研究

柔性滑板生产线是一种采用柔性摩擦驱动的汽车装配输送线,可提高装配效率和系统自由度。无接触供电技术(Contactless Power Supply,CPS)是一种安全、灵活、有效的新型供电技术。在柔性滑板生产线中运用CPS技术,可以提升滑板的速度和负载能力,人机协调性良好,实现了高效、柔性的随行装配,提升了物流自动化程度。     

A hybrid algorithm for allocating tasks,operators, and workstations in multi-manned assembly lines

In a car, there are approximately 30,000 parts produced by many different industries. This is due to the complexity and enormity of the automotive industry chain. The vehicle assembly process comprises welding, painting, prefabrication, and final entire-vehicle assembly. The assembly line has the largest labor force, which should be arranged and balanced to increase production efficiency and reduce labor force requirements. Unlike traditional studies on assembly line balancing problems (ALBPs), this study considers the characteristics of the automotive industry, such as multi-manned workstations, minimization in terms of the numbers of operators and workstations for streamlined production, budget constraints, the optimization of both task and operator allocation among workstations, and the determination of the start/end processing time of each task at different workstations. To address these NP-hard problems, a hybrid heuristic approach that combines the procedure of building feasible balancing solutions and the simulated annealing algorithm is proposed to map out an optimal line balancing plan for multi-manned workstations and to reduce the required workspace for shop operations. Based on the design and analysis of experiments, the effects of the maximum number of allowed operators per workstation and those of the cycle time on ALBP solutions are explored. The optimal combination of algorithm parameters is also determined. The results of this study can serve as a practical reference in planning the allocation of tasks, workstations, and operators in the industry.     

基于PLC的空压机远程监控系统的设计与实现

随着技术的发展,我国的许多设备严重老化,即将面临淘汰。在现代化的企业中,要求空压机的控制装置有较高的自动化水平,采用微机控制是空压机发展的必然趋势。它可以减轻操作人员的劳动强度,对空压机的可靠安全运行起到保证和促进作用。东风商用车公司总装配厂有3条整车组装线和一个检测车间,车间所需要的压缩空气由3对空气压缩机和冷干机来提供,分别位于三个空压机房。本课题主要是要研究开发基于组态王软件的监控界面。整个系统是用PLC进行控制,组态王软件进行监控。PLC主要控制空压机的启动和停止,组态王用于读取压力,以便我们随时了解系统信息,进行调整,确保生产程序的正常运行。     

LPC4320双核处理器在支架电液控系统中的应用

随着煤矿自动化、智慧矿山的快速发展,工作面支架电液控系统的功能也更加复杂。为了满足支架电液控系统在实时姿态控制、数据传输以及与工作面采煤机、刮板机、视频监控等系统联动方面的要求,本文基于LPC4320异构双核处理器开发一种新型支架控制器。既有强大的数据处理能力,满足多通道传感器实时信号采集与处理以及基于数字信号的支架控制功能的需求,又具有强大的控制能力,实现支架远程控制、自动控制、多设备联动控制等功能。     

变电站综合自动化系统远动指标统计算法

为了提高变电站综合自动化系统远动指标统计分析能力,需要对变电站综合自动化系统远动指标进行统计处理,提出一种基于模糊聚类和关联规则挖掘的变电站综合自动化系统远动指标统计分析算法。采用分段检验分析方法进行变电站综合自动化系统远动指标的信息采集,提取变电站综合自动化系统远动指标的关联规则特征量,结合模糊融合聚类方法进行变电站综合自动化系统远动指标的大数据聚类处理,采用互信息特征检测方法,进行变电站综合自动化系统远动指标的大数据挖掘和信息检测,根据特征检测结果采用分段模糊聚类方法进行特征归类处理,在聚类空间中实现变电站综合自动化系统远动指标统计分析。仿真结果表明,采用该算法进行变电站综合自动化系统远动指标的统计分析能力较强,大数据聚类性较好,提高了指标统计分析和决策能力。     

A comparison of adaptive and adaptable automation under different levels of environmental stress

The effectiveness of different forms of adaptive and adaptable automation was examined under low- and high-stress conditions, in the form of different levels of noise. Thirty-six participants were assigned to one of the three types of variable automation (adaptive event-based, adaptive performance-based and adaptable serving as a control condition). Participants received 3 h of training on a simulation of a highly automated process control task and were subsequently tested during a 4-h session under noise exposure and quiet conditions. The results for performance suggested no clear benefits of one automation control mode over the other two. However, it emerged that participants under adaptable automation adopted a more active system management strategy and reported higher levels of self-confidence than in the two adaptive control modes. Furthermore, the results showed higher levels of perceived workload, fatigue and anxiety for performance-based adaptive automation control than the other two modes. PRACTITIONER SUMMARY: This study compared two forms of adaptive automation (where the automated system flexibly allocates tasks between human and machine) with adaptable automation (where the human allocates the tasks). The adaptable mode showed marginal advantages. This is of relevance, given that this automation mode may also be easier to design.     

鞍钢冷轧厂电解清洗线综合自动化控制系统

为了提高生产线的自动化控制水平,根据冷轧厂电解清洗线的工艺要求及控制特点,将西门子最新产品和技术应用在冷轧板处理线自动化控制系统。设计了基于西门子S7—400PLC、WINCC监控软件、工业以太网、Profibus-DP现场总线和工控机的综合自动化控制系统。将西门子全集成自动化（Totally Integration Automation—TIA）的思想贯穿于系统配置设计的始终,使传动控制系统、过程控制系统、上位机系统集成到PCS7,使系统配置更简捷、可靠、有效,调试更方便,实现了清洗生产过程的优化控制、优化运行和优化管理,取得了明显的应用成效。     

注塑生产中残留物监测系统的研究

将设计一种将摄像头应用于注塑机残留物的监测中.该系统能够通过摄像头去采集注塑现场的信息,利用单片机微处理系统对采集的图像数据进行实时地处理,最后达到自动地去控制注塑机的运转功能,提高注塑机的自动化程度.主要结合了图像处理算法和单片机的优点,并进行不断地优化系统.试验结果表明该系统能够实时高效地进行自动监测.