供应链需求替代与生产流程柔性联合决策研究

通过在供应端引入生产流程柔性或在需求端针对顾客需求采用产品替代均能一定程度上应对需求不确定性对企业运营带来的负面影响,在考虑存在生产流程柔性以及需求替代成本,且只有一定比例的消费者接受产品替代的情形下,文章分析了刚性结构、需求替代、需求替代与部分生产流程柔性以及生产流程全柔性4种情境,研究了生产流程柔性与需求替代两者之间的相互影响及企业最优柔性结构的选择问题,并通过数值分析给出了相关参数设置下的最优选择结果,为现实中企业的柔性结构选择提供了一定的理论基础.     

工序顺序柔性的作业车间调度问题的改进遗传算法求解

针对在工艺设计中提供工序顺序柔性的作业车间调度问题,总结了该问题中柔性工序顺序的类型和特点,并提出了一种求解该问题的改进遗传算法.以尽可能缩短制造周期为目标,结合问题特点,改进了染色体的编码方式,在常用的基于工序顺序的编码方法上融入了基于柔性工序顺序的编码方法,并据此设计了相应的交叉、变异等操作,防止遗传过程中不可行解的产生,避免染色体修复,提高求解效率.最后以MATLAB为工具用某轴承公司的实际生产数据对该算法进行了仿真.通过与不考虑工序顺序柔性的作业车间调度问题遗传算法求解结果进行对比,证明了该算法可行性和有效性.     

制造云服务组合柔性的四维属性测度方法

云制造环境下服务资源进行动态组合时不可避免地遇到内、外部环境的不确定性,这些不确定性因素直接影响到制造云服务组合的执行成本、效率和质量。为了有效提升制造云服务组合的柔性,需要对其柔性能力进行测度。在假定某待选云服务集中的各服务资源能够以不同的效率替代完成任务的基础上,建立了考虑制造云服务组合柔性的效率柔性、冗余柔性、路径柔性和任务柔性的四维属性测度方法。最后,结合具体算例对该方法的应用过程进行了分析。     

自适应蚁群算法及其在多约束多目标柔性Job-Shop调度中的应用

实际生产系统的车间作业调度一般是多约束多目标柔性Job-Shop调度,比经典的Job-Shop调度更复杂,存在多约束、多目标、动态柔性、建模复杂等特性.建立了多约束多目标柔性Job-Shop调度模型,提出了一种自适应蚁群算法,采用自适应机制和遗传原理防止算法过早停滞和加快收敛速度.西安航空发动机(集团)有限公司制造单元调度实例表明,提出的自适应蚁群算法是求解多约束多目标柔性Job-Shop调度的有效方法.     

一类幂等半环上线性方程组的解法

极大-极小-加系统规划的全局优化可用于通信网络、柔性制造、对策博弈等实际系统,而幂等半环上线性方程理论在极大-极小-加系统规划的全局优化的研究中起着关键的作用.对于一类幂等半环上的非齐次线性方程组,引入列满秩矩阵与控制向量概念,并分别给出解的存在性和惟一性充分必要条件以及求解方法.     

模糊环境下的柔性工作车间调度模型的研究

本首先引入了柔性生产系统下的调度过程中存在的不确定性问题，接着对存在模糊操作时间间隔的柔性工作车间调度问题及相关概念进行了描述，并且给出了以最小makespan为目标的基于模糊逻辑和遗传优化的调度模型，最后通过实例验证了模型的可行性。     

非线性极大极小系统全局优化算法的分析

非线性极大极小系统的全局优化可用于柔性制造和智能交通的决策与控制.实现了非线性极大极小系统的全局优化算法的仿真,并进行了计算时间分析.数值实验表明了全局优化算法的可行性.算法的计算时间主要由系统的优化极大射影矩阵数目决定,而优化极大射影矩阵数目与系统解析式中单极大式的系数紧密相关,系数取值越分散,简约极大射影矩阵的效果越好,计算效率越高.     

技术柔性、柔性生产与柔性技术的价值

在产品市场和要素市场存在不确定性的条件下,将企业的生产行为和技术柔性水平的选择纳入一个统一框架进行分析,给出了柔性技术的价值函数及其特征.结果表明,给定技术柔性水平,柔性生产行为价值不会低于非柔性生产行为的价值;给定生产行为,柔性技术的价值不会随着其柔性增加而降低.进一步,在一定条件下,柔性生产行为比非柔性生产行为更具价值,柔性技术的价值随着其柔性水平的增加而增加.     

粒子群遗传混合算法求解考虑传输时间的FJSP

在某些生产制造场景中,工件在不同机器间的传输时间对车间调度的总拖期具有重要影响,本文基于此扩展了总拖期最小的柔性作业车间调度模型。针对问题模型的复杂性,采用粒子群优化算法和遗传算法的混合算法进行求解。在初始化过程以一定概率优选加工时间和传输时间短的机器并排除调度频繁的机器,使种群在保持多样性的前提下尽量选择优化结果好的个体;采用线性调整的方式动态改变交叉概率和变异概率的值,使种群在遗传算法的不同阶段具有不同的搜索强度;采用粒子群优化算法进行局部搜索,弥补了遗传算法局部搜索能力的不足。最后采用本文方法和其他方法求解柔性作业车间调度问题实例,并对比不同水平层次传输时间下的总拖期,验证了本文方法的有效性。     

基于PLSR的多级制造过程关键质量特性识别方法

为解决多级制造过程关键质量特性识别中多质量特性之间的相关性问题,将偏最小二乘回归方法(Partial Least Squares Regression, PLSR)引入模型构建与分析中。首先应用状态空间方法建立多级制造过程关键质量特性识别模型,进而利用PLSR方法解决质量特性间的多重共线性问题并进行模型分析,识别关键质量特性,最后以卷烟生产过程为例介绍了该方法的应用。实例表明,该方法不仅可以有效识别多级制造过程关键质量特性,而且能够建立各级过程的输出质量对最终产品质量的影响及其质量特性之间相互关系的模型,反映多级生产过程的结构特征和各级过程质量特性之间的因果关系,为多级制造过程质量分析与控制提供依据。     

基于卷积神经网络的智能制造过程质量异常诊断

针对现有方法在智能制造过程中诊断能力有限和识别精度不高的问题,提出了一种与智能制造过程相适应的基于卷积神经网络的质量异常诊断模型。首先建立基于实时数据的过程质量图谱,以精准表达制造过程运行状态。其次,构建用于识别质量图谱的卷积神经网络诊断模型。最后,利用滑动窗口取值的方式对当前过程运行状态进行动态诊断,并通过某球磨过程验证了所提方法的有效性与实用性。结果表明,所提方法优于传统浅层模型,能够有效的对过程异常状态进行识别与诊断。     

Production set of failure prone flexible manufacturing systems 1

For a flexible manufacturing system, determining the feasible production set at a given time is essential for production management. In this paper, we propose methods for estimating the production set for a general multi–part type failure prone flexible manufacturing system. We also discuss how to get an open loop control that can ensure the system producing at the margin of its expected production set and how to estimate the corresponding variance of the expected production set. Some special flexible manufacturing systems are discussed where we also suggest some simpler approximations. Numerical examples are presented to illustrate our algorithm     

Long term capacity decisions in uncertain markets for advanced manufacturing systems incorporating scope economies

By examining the literature in the field of manufacturing flexibility many researchers have located several form of flexibility by distinguishing them into strategic and operational flexibility forms. Furthermore, many measures and design methods have been proposed for flexible manufacturing systems. Surely scope economies are one of the most important strategic form of flexibility in manufacturing systems and their strategic impact has been acknowledged by the very beginning of the flexible manufacturing era. However, despite several researches are available to address scope economies measurement and design methodologies, very few researches investigate their economic convenience in front of dedicated manufacturing systems depending on the competitive market conditions.This paper proposes a theoretical model whose main aim is the general understanding of the convenience conditions of scope economies-based manufacturing systems. The results of the theoretical model are very interesting, because they locate market conditions that make scope economies manufacturing systems less profitable than dedicated manufacturing ones; moreover, the proposed model sets some general criteria to guide the entrepreneur in making right investment decision regarding this kind of manufacturing investments. Such results can explain the reason of many failures of flexible manufacturing systems and it suggests the use of this kind of approach to investigate other flexibility forms of manufacturing systems. The ultimate goal of this research is the construction of a Decision Support System for supporting the entrepreneur in making decision on Advanced Manufacturing Systems investment decisions.     

Managing production with flexible capacity deployment for serial multi-stage manufacturing systems

This paper presents a model for serial multi-stage manufacturing systems facing variability from two sources. One source is demand uncertainty; the other is manufacturing uncertainty associated with all manufacturing stages. A production control policy based on the planned lead time and the manufacturing capacity requirement is developed. It is shown that this production control policy has the effect of reducing the variance of production output for all manufacturing stages. Some specific analyses are provided to illustrate the production control policy developed. The model developed provides a vehicle for examining the interrelationships among the production output, the planned lead time and the actual manufacturing flow time. The risk-pooling value over both demand randomness and manufacturing uncertainty, which is achieved through consolidating some manufacturing capacity and deploying flexible capacity among the manufacturing stages, is analyzed. This risk-pooling value can be realized in the form of either reduced manufacturing flow time or increased effective capacity to meet more demand. It is shown that the risk-pooling value increases as the planned lead time decreases.     

Economically study regarding modernizing of the final working of the car radiators through implementation of an articulated robot in a flexible manufacturing cell

In this paper the authors purpose the conception and modelling of a possible application in a circular flexible manufacturing cell. This flexible cell is composed from five manufacturing points for realizing the final technological itinerary of a type of radiator. This flexible manufacturing cell is served by an industrial articulated robot, which possess in his cinematic chain three degrees of freedom, type RRT. In virtue of real values of the functional parameters which are input data in the analysis of the flexible manufacturing cell, had been dignify the cost of the flexible manufacturing cell, determining the value of the included industrial robot in the system and the value of the entire flexible cell where the robot realize the manipulating process of the radiators. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

智能制造环境下的备件生产与运输协同调度问题研究

智能制造和即时配送环境下的备件生产与运输协同调度问题是目前国内研究的一大热点,这是因为备件供应链响应速度已成为当前备件制造企业赢得客户的关键因素。为了提高客户满意度,尽可能缩短从客户下达定制化生产订单到订单配送完成的时间,本文建立了以所有客户总等待时间最短为目标的混合整数规划模型和集合覆盖模型,推导了最优解性质,并设计改进的分支定价算法求得最优解。通过将小规模算例结果与CPLEX进行对比,验证了模型和算法的有效性。多组算例测试结果表明,所提出的模型和算法可以有效提升智能制造环境下的备件供应链运作效率。     

Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries

In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance.     

The optimality of balancing workloads in certain types of flexible manufacturing systems

Symmetric mathematical programming is used to analyze the optimality of balancing workloads to maximize the expected production in a single-server closed queuing network model of a flexible manufacturing system (FMS). In particular, using generalized concavity we prove that, even though the production function is not concave, balancing workloads maximizes the expected production in certain types of m-machine FMS's with n parts in the system. Our results are compared and contrasted with previous models of production systems.     

Dynamic analysis of repetitive decision-free discreteevent processes: The algebra of timed marked graphs and algorithmic issues

A model to analyze certain classes of discrete event dynamic systems is presented. Previous research on timed marked graphs is reviewed and extended. This model is useful to analyze asynchronous and repetitive production processes. In particular, applications to certain classes of flexible manufacturing systems are provided in a companion paper. Here, an algebraic representation of timed marked graphs in terms of reccurrence equations is provided. These equations are linear in a nonconventional algebra, that is described. Also, an algorithm to properly characterize the periodic behavior of repetitive production processes is descrbed. This model extends the concepts from PERT/CPM analysis to repetitive production processes.     

Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics

Manufacturing flexibility improves a firm’s ability to react in timely manner to customer demands and to increase production system productivity without incurring excessive costs and expending an excessive amount of resources. The emerging technologies in the Industry 4.0 era, such as cloud operations or industrial Artificial Intelligence, allow for new flexible production systems. We develop and test an analytical model for a throughput analysis and use it to reveal the conditions under which the autonomous mobile robots (AMR)-based flexible production networks are more advantageous as compared to the traditional production lines. Using a circular loop among workstations and inter-operational buffers, our model allows congestion to be avoided by utilizing multiple crosses and analyzing both the flow and the load/unload phases. The sensitivity analysis shows that the cost of the AMRs and the number of shifts are the key factors in improving flexibility and productivity. The outcomes of this research promote a deeper understanding of the role of AMRs in Industry 4.0-based production networks and can be utilized by production planners to determine optimal configurations and the associated performance impact of the AMR-based production networks in as compared to the traditionally balanced lines. This study supports the decision-makers in how the AMR in production systems in process industry can improve manufacturing performance in terms of productivity, flexibility, and costs.