Modelling of material handling systems for facility design in manufacturing environments with job-specific routing

Traditionally, flow times distance is used as a surrogate for cost in facility design. However, this performance measure does not fully capture the impact of facility design decisions on operational performance measures such as cycle time and work-in-progress in the system, which are often more meaningful for managers, especially in a manufacturing environment. To better measure operational performance, modelling of material handling systems using a queueing network must be integrated in the facility design process. A number of approaches are discussed in the facility design literature for modelling material flow using queueing networks. In these approaches, Poisson arrival or Markovian job routing assumptions have been used. However, for many manufacturing environments, these assumptions lead to an inaccurate estimation of the material handling system's performance and thus lead to poor facility designs. Incorporating more general queueing results for non-Markovian systems is difficult, however, because the facility design process must investigate a large number of potential solutions and thus the results from the queueing models for the material handling system must be quickly obtained. In this paper, the need for more general queueing models of material handling systems in facility design is confirmed. Then, an approach based on multi-class queueing models is adapted to capture the change in variability of the system performance caused by both different arrangements of workstations in the facility and different arrival processes to the workstations due to the job routing in a computationally efficient manner. The proposed modelling approach is shown to provide more accurate results than previous methods used in facility design based on numerical comparisons with results from discrete-event simulation.     

State-dependent models of material handling systems in closed queueing networks

A comprehensive algorithmic analysis of finite state-dependent queueing models and exponentially distributed workstations is formulated and presented. The material handling system is modeled with finite state-dependent queueing network M/G/c/c models and the individual workstations are modeled with exponentially distributed single and multi-server M/M/c queueing models. The coupling of these queueing models is unique via the material handling structure. The performance modeling of the systems for series, merge, and split and other complex network topologies are included so as to demonstrate the type of topological network design that is possible with these incorporated material handling systems. Of some importance, it is shown that these integrated M/M/c and M/G/c/c networks have a product form when the population arriving at the M/G/c/c queues is controlled. Numerous experimental results demonstrate the efficacy of our approach for a variety of contexts and situations.     

Optimal pickup point location on material handling networks

The optimal location of a pickup point on a material handling network is considered. The pickup point is defined as the material exchange point between the material handling system (MHS) and a station. The problem is defined as that of choosing the location of the pickup point to minimize the total cost of material movement in the MHS. A facility location model on directed networks has been developed, and strongly polynomial solution methods are presented.     

THROUGHPUT MAXIMIZATION IN FLEXIBLE MANUFACTURING SYSTEMS

Maximizing the throughput (or revenue generation) rate has become one of die most important criteria in die design and management of Flexible Manufacturing Systems (FMSs). This paper develops dynamic part-allocation policies for FMSs having finite storage capacity at each work station. Maximizing the throughput rate means that the resulting queueing network model has a state-dependent arrival process; therefore, product-form solutions do not hold. Consequently, several alternative modeling approaches are described and formulated for deriving die optimal part-routing policies. One of these optimal policies is based on a new initiated-suspension part-routing strategy. This strategy results in a reduced load on the material handling system while increasing die expected throughput (or revenue generation) rates of the manufacturing work stations. We also propose several efficient closed-loop heuristic policies that exploit die response structure of die optimal policies. These heuristic policies are of practical significance because they are extremely easy to compute and to implement, while die resulting FMS performance is nearly optimal.     

Material handling considerations in the FMS loading problem with full routing flexibility

This study exploits machining and routing flexibility to effectively deal with the material handling requirements resulting from a frequently changing demand mix in a manufacturing system where material handling is a bottleneck. For this purpose, the objective function of the operation and tool loading problem is selected as the minimisation of the total distance traveled by parts during their production. Versatile machines and the flexible process plans offer full routing flexibility that enable the same workpiece to be processed using alternative sequences of operations on alternative machines. Three mathematical programming (MP) models and a genetic algorithm (GA) are proposed to solve this problem. The proposed MP formulations include a mixed-integer nonlinear programming (MINLP) model and two mixed-integer programming (MIP) models, which offer different representations for the flexible process plans. The GA is integrated with linear programming for fitness evaluation and incorporates several adaptive strategies for diversification. The performances of these solution methods are tested through extensive numerical experiments. The MP models are evaluated on the basis of the exact solutions they yield as well as how they lend themselves for GA fitness evaluation. The GA–LP integration works successfully for this hard-to-solve problem.     

周转量在物流运输成本分析中的应用

引入运输周转量叠加累计的方法,将物流运输成本量化运用于总图方案比较中。通过换算后的平均运输距离来分析高阶段总平面布置方案的合理性,继而调整整体布局和运输距离,优化方案,实现总图与运输的完美统一;同时,也增强方案实施的可行性,赢得市场。     

智能制造系统AGV小车及缓冲区容量仿真优化

具有MHS(material handling system)的智能制造系统AGV(automated guided vehicle)小车及缓冲区最大容量配置优化,属于典型的非线性整数规划问题。由于约束无法用封闭形式表达,因此较难获得问题的精确解。为此,本文提出了仿真优化的方法以获得问题的近似解。首先,对AGV小车及缓冲区最大容量配置优化问题进行了描述;其次,基于Em plant平台建立了具有MHS的智能制造系统仿真模型;然后,基于不同的优化目标,提出了3种仿真优化方法;最后,通过仿真试验对上述3种方法进行了分析与比较。分析表明,本文提出的方法及优化结果,可为企业配置AGV小车及缓冲区最大容量提供决策支持。     

SLP在摩托车企业厂房布局设计研究中的应用

基于系统布置设计(SLP)原理,以某摩托车企业新厂房布置设计为例,运用物流分析和作业单位相互关系图分析各车间之间的物流关系和非物流关系,形成作业单位综合相互关系图。运用因素评价法从物流效率、空间利用率、管理方便性等方面对两个可行的布置方案进行了分析比较,获得较优方案。通过与该企业原厂区的对比分析,新厂区的布置方案可使该企业的生产效率提高18%,能满足该企业新厂区1600台/d的生产能力要求。     

Bionic design methodology for wear reduction of bulk solids handling equipment

Large-scale handling of particulate solids can cause severe wear on bulk solids handling equipment surfaces. Wear reduces equipment life span and increases maintenance cost. Examples of traditional methods to reduce wear of bulk solids handling equipment include optimizing transport operations and utilizing resistant materials. To our knowledge, the so-called bionic design has not been utilized. Bionic design is the application of biological models, systems, or elements to modern engineering. Bionic design has promoted significant progress on the development of engineering products and systems. In order to use bionic design for wear reduction of bulk solids handling equipment surfaces, this paper introduces bionic design to bulk solids handling on the basis of analogies between biology and bulk solids handling. In addition, a bionic design methodology for the wear reduction of bulk solids handling equipment surfaces is formulated. Based on the bionic design methodology, two bionic models used for abrasive and erosive wear reduction of bulk solids handling equipment surfaces are proposed.     

Modeling for flexible manufacturing systems with an FMS blocking mechanism and a BDSM job routing

We consider a Flexible Manufacturing System (FMS) which is composed of a set of workstations, a common buffer and a Material Handling System (MHS). Each workstation includes a limited input buffer, several machines and a limited output buffer. The MHS consists of several carts moving jobs among the workstations according to the process paths required by the jobs. The carts treat blocked jobs in accordance with a new blocking mechanism, called the 'FMS blocking mechanism'. The function of the common buffer is to temporarily store blocked jobs. Such an FMS is formulated as an open queueing network, in which the MHS is modeled as a central station routing jobs to the workstations. In the model, the machines process jobs with an exponentially distributed processing time, and the carts route jobs to the workstations following a 'Blocking Depended Static Markov (BDSM) job routing' with an exponentially distributed routing time and treat blocked jobs in accordance with the FMS blocking mechanism. It is shown that the equilibrium state distribution of the model has a product-form solution. The blocking probabilities are obtained by computing a fixed point problem whose solution is revealed by an iterative algorithm. Moreover, it is shown that the throughputs of the workstations are independent of the spaces on the local buffers at the workstations. Several numerical examples are presented.     

Gradient design of metal hollow sphere (MHS) foams with density gradients

Metal hollow sphere (MHS) structures with a density gradient have attracted increasing attention in the effort to pursue improved energy absorption properties. In this paper, dynamic crushing of MHS structures of different gradients are discussed, with the gradients being received by stacks of hollow spheres of the same external diameter but different wall thicknesses in the crushing direction. Based on the dynamic performance of MHS structures with uniform density, a crude semi-empirical model is developed for the design of MHS structures in terms of gradient selections for energy absorption and protection against impact. Following this, dynamic responses of density graded MHS foams are comparatively analyzed using explicit finite element simulation and the proposed formula. Results show that the simple semi-empirical model can predict the response of density gradient MHS foams and is ready-to-use in the gradient design of MHS structures.     

A heuristic approach on the facility layout problem based on game theory

Facility layout problems are related to the location of all facilities in a plant. Numerous research works related to facility layout have been published. The applicability of these various existing models may be limited by the fact that they all ignore competitive reactions to one's actions. In addition to external competitors, some internal problems of system such as material handling system design affect layout designs. For considering these effects, some researchers have investigated multi-objective approaches that in most cases lead to the optimisation of a weighted sum of score functions. The poor practicability of such an approach is due to the difficulty of normalising these functions and quantifying the weights. To the extent that competitors do react to a firm's actions and also the facility layout problem considers several conflicting objectives by distinct decision makers in the firm, the existing models may be oversimplifications of reality. In this paper, we modelled such a facility layout problem with conflicting objectives under a duopoly Bertrand competition as a game and solved it with a proposed simulated annealing meta-heuristic. Results obtained from solving some numerical examples confirm the effectiveness of the proposed model for the layout design.     

EXCITE: Expert consultant for in-plant transportation equipment

The cost of handling material is a vital factor in the facilities design process, whether it is for a new facility or for the redesign of an existing facility. Handling activities generally account for 30 to 40% of production costs, but in some industries they can be as high as 70%. Well designed handling systems are thus crucial for reduced costs and increased profits.

A key task in the material handling system design process is the selection and configuration of equipment for transport and storage in a facility. Material handling equipment selection is a complex, tedious task, and there is usually more than one good answer for any particular situation. A number of good quantitative techniques are available to aid the industrial engineer in determining layout design with the aim of reducing material handling cost. Unfortunately, there are few tools other than checklists to aid the engineer in the selection of appropriate, cost-effective material handling equipment. Analytical models are not often applied in industry because they generally consider only quantifiable factors such as cost and utilization and are difficult to implement.

This paper describes a knowledge-based approach for addressing the major factors that influence equipment selection. The research effort involved two major activities: compilation of a knowledge base from an in-depth review and modification of traditional checklists and published literature on equipment selection; and development of a prototype expert system for material handling equipment selection.     

Bi-objective facility expansion and relayout considering monuments

In this paper, the unequal area facility expansion and relayout problem is studied. The facility relayout problem is important since both manufacturing and service entities must modify their layouts over time when their operational characteristics change. A bi-objective approach is proposed to solve the relayout problem for cases of both a fixed facility area and an expanded facility area. Material handling costs and relayout costs are minimized using a tabu search meta-heuristic optimizer. This heuristic randomly alternates the objective function between the two objectives of the problem in each step and, by doing so, eliminates the difficulty of weighting and scaling the two objectives. The approach is flexible in handling various aspects of the problem such as stationary portions of departments (i.e., monuments), addition of new departments, and changes in existing department and facility areas. Computational experiments show that the bi-objective tabu search approach is effective and tractable. The use of the Pareto front of designs is demonstrated by showing a few approaches to analyzing the trade-offs between initial costs (relayout cost) and ongoing expenses (material handling costs).     

Minimizing work-in-process and material handling in the facilities layout problem

We consider the plant layout problem for a job shop environment. This problem is generally treated as the quadratic assignment problem with the objective of minimizing material handling costs. Here we investigate the relationship between material handling costs and average work-in-process. Under restrictive assumptions, an open queueing network model can be used to show that the problem of minimizing work-in-process reduces to the quadratic assignment problem. In this paper, we generalize these results through a simulation model, and develop a simple secondary measure which allows us to select the layout that minimizes average work-in-process levels from among solutions that are similar with respect to the objective function for the quadratic assignment problem.     

Performance analysis of an inbound call center with skills-based routing

Many call centers provide service for customers of different classes with differently qualified groups of agents. Since call arrivals and call handling times are random in inbound call centers, we investigate queueing models for their performance analysis. This paper describes a Markov queueing model with two customer classes and three groups of specialized or flexible agents. The mean call handling time may depend on the respective customer class as well as on the agent group serving this call. The customers are assumed to be impatient. We consider skills-based routing with priority-based rules and derive both steady-state probabilities and performance measures. We present some numerical experiments and show the impact of different mean processing times. The influence of the allocation of the agents into the three groups is analyzed for different levels of patience.Correspondence to: Raik Stolletz . R. Stolletz, S. Helber: The authors thank the anonymous referees for their helpful comments and suggestions.     

Design of an automated guided vehicle-based material handling system for a flexible manufacturing system

Automated guided vehicle (AGV)-based material handling systems (MHSs), which are widely used in several flexible manufacturing system (FMS) installations, require a number of decisions to be made. These include the number of vehicles required, the track layout, traffic pattern along the AGV tracks, and solving traffic control problems. This paper addresses the key issues involved in the design and operation of AGV-based material handling systems for an FMS. The problems arising from multi-vehicle systems are analysed, and strategies for resolving them are examined using analytical and simulation models.     

Analysis of finite-buffer state-dependent bulk queues

In this paper, we consider a general state-dependent finite-buffer bulk queue in which the rates and batch sizes of arrivals and services are allowed to depend on the number of customers in queue and service batch sizes. Such queueing systems have rich applications in manufacturing, service operations, computer and telecommunication systems. Interesting examples include batch oven processes in the aircraft and semiconductor industry; serving of passengers by elevators, shuttle buses, and ferries; and congestion control mechanisms to regulate transmission rates in packet-switched communication networks. We develop a unifying method to study the performance of this general class of finite-buffer state-dependent bulk queueing systems. For this purpose, we use semi-regenerative analysis to develop a numerically stable method for calculating the limiting probability distribution of the queue length process. Based on the limiting probabilities, we present various performance measures for evaluating admission control and batch service policies, such as the loss probability for an arriving group of customers and for individual customers within a group. We demonstrate our method by means of numerical examples.     

Integrating occupational health and safety in facility layout planning,part I: methodology

An influential factor affecting the efficiency of a manufacturing facility is its layout. In a production facility, measure for efficiency can be based on the total cost of transporting the items between different departments and throughout the facility. However, other factors may influence efficiency of the manufacturing facility too. As such are: supporting the organisation's vision through improved material handling, material flow and control; effectively assigning people, equipment, space and energy; minimising capital investment; adaptability and ease of maintenance; as well as providing for employee safety and job satisfaction. By incorporating health and safety measures in the initial design of a facility layout, the organisation may avoid money and manpower loss resulting from industrial accidents. This paper proposes a facility layout planning methodology which integrates the occupational health and safety (OHS) features in the early design of a facility layout. The model considers transportation cost in the facility as well as safety concerns. By this means, the OHS issues are reflected prior to the construction of a facility.     

基于有限单元柔度法和刚度法的几何非线性空间梁柱单元比较研究

分别基于有限单元柔度法和有限单元刚度法二阶分析理论,采用纤维模型梁柱单元编制了钢筋混凝土杆系结构二阶非线性分析程序;分别采用这两种方法对几个典型试验实例进行了计算机模拟分析,通过模拟分析结果的对比,对有限单元柔度法与有限单元刚度法处理几何非线性问题的效果与效率进行了比较研究。结果表明:对于几何非线性问题,尤其是对于处理下降段(非稳定阶段)问题,基于柔度法的梁柱单元无论从计算效率还是计算效果上都明显优于基于刚度法的梁柱单元,有限单元柔度法是目前处理杆系结构材料与几何双重非线性问题最为有效的分析方法。