Optimizing dock configuration and staffing in decentralized receiving

In manufacturing facilities, shipping and receiving traditionally have been concentrated in one or two areas of the building. The widespread introduction of just-in-time shipping policies in US manufacturing companies during the past 15 years, as well as the common use of decentralized receiving in the Japanese automobile industry, has motivated the consideration (and occasionally the adoption) of dock configurations to support decentralized receiving (also known as perimeter receiving). By providing multiple access points along the perimeter of the building, decentralized receiving generally reduces the time and cost associated with moving purchased parts to the locations within the facility where they are used, but also results in increased cost of construction, maintenance, and operation for docks and associated truck access/egress, as well as additional interior floorspace requirements. We develop an optimization-based procedure to determine which of several possible dock areas to construct, how many doors or gates each should have, how many unloading and internal material handling staff should be assigned to each group, and which inbound materials each group should handle. We consider the amortized cost of constructing and equipping the docks, the amortized cost of material handling equipment to support the unloaders and material handlers, the cost of operating the material handling equipment, and labor costs for both unloading and internal material handling.     

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.     

Kanban number optimisation in a supermarket warehouse feeding a mixed-model assembly system

Following just-in-time principles, a growing number of manufacturers are adopting the so-called supermarket concept. Supermarkets are decentralised storage areas scattered throughout the shopfloor that serve as an intermediate store for parts required by nearby assembly lines. From these stores, a certain number of handling operators deliver parts from the supermarket to, and collect empty bins from, assembly stations. Finally, they return to the supermarket and are refilled for their next tours. The assembly stations are typically refilled from the supermarket through the constant replacement of the consumed parts pulled by the kanban system. Considering a mixed model assembly system composed of different assembly lines, feeding problems can occur as an effect of the replenishment lead time, of the production mix variation, of the commonality between the different models assembled. The aims of this paper are (i) to highlight how the supermarket/multi-mixed assembly-line system presents specific attributes that prohibit the simple application of well-known kanban dimensioning formulations and (ii) to provide an innovative procedure to optimally set all decision variables related to such a feeding system.     

A multi-objective mixed-integer programming model for a multi-floor facility layout

We consider a multi-floor facility layout problem in which the overall length and width of the facility, the size and location of each department, the number and the location of elevators and the number of floors in the facility are all modelled as decision variables. We adapt a linear approximation scheme to represent the area of each department. We consider two objective functions in our model, namely minimising material handling and facility building costs, and propose a lexicographic ordering technique to handle multiple objectives. The numerical experiments show that the slack used in the lexicographic ordering approach has a significant impact on the optimal solution. The experiments also show that the material handling cost can be significantly reduced in a multi-floor facility compared with a single-floor facility.     

Work-in-process space allocation: a model and an industrial application

This paper presents a model for allocating storage space to inventory in a way that minimizes the cost of material handling. The space allocation problem is modeled as a generalized transportation problem; however, transporting material within the facility is the focus. The basic formulation of the model considers material type, material flow transitions, and distance transported. The model is extended to determine production levels for multiple products such that additional material handling costs (i.e., load/ unload times) are minimized. Applications of the just-in-time (JIT) concept and material handling in the job shop environment are discussed. Finally, an industrial case study is presented     

Assembly system facility design

This paper addresses the design of an assembly system facility consisting of multiple assembly lines of different shapes. In such a design problem there are two conflicting objectives: (i) to minimize the overall area of the facility; and (ii) to maximize the efficiency of the material handling transportation system. We first address the optimization problem of objective (ii) when replacing objective (i) with a constraint on the facility area. We propose a mixed-integer linear program to determine the layout of a facility with given dimensions and with given assembly line areas and shapes (that cannot be changed due to technological considerations). In the layout model, the physical placement of each line within the facility is a decision variable. The objective function of the layout model is to minimize the distances traveled by material flow. Our performance analysis provides an indication of the maximal problem size that can be solved in a reasonable amount of time and we examine the effect of the problem parameters on the solution run time. This layout model is then incorporated into an efficiency frontier approach for facility design to address both objectives. Examples are presented to illustrate the use of the proposed facility design model.     

A two-phase procedure for duplicating bottleneck machines in a linear layout,cellular manufacturing system

We discuss a two-phase procedure for duplicating bottleneck machines in a cellular manufacturing system. Given a preliminary solution by a clustering technique, the first phase solves a cellular layout problem in which it assigns machine-cells to locations to minimize the total inter-cell material handling costs that result from the bottleneck parts. The purpose of this phase is to find an optimal linear layout of cells. The second phase finds the bottleneck machines that need to be duplicated to minimize the costs. A binary (integer) linear programming model is developed in this phase to minimize the total duplication costs and material handling costs (if not duplicated). Finally, a decision is made as to whether a solution with bottleneck machines, or duplication of bottleneck machines to avoid the bottleneck problem is to be accepted. An example is demonstrated to show how such a bottleneck problem in cellular manufacturing is solved.     

Research issues on factors influencing the choice of kitting versus line stocking

Kitting and line stocking systems are common alternatives for component storage in assembly environments. Despite the need for knowledge about when and where each system would be applicable in industry, research on the choice of kitting versus line stocking systems in industry is quite sparse. This paper identifies a number of research issues that might influence this system choice decision based on an analysis of the kitting operations and the potential move to line stocking at an electronics assembly company. Research questions are presented in the areas of product characteristics (volume, variety, and size), storage and material handling, production control, performance impact, and implementation. The issues identified here highlight factors that might influence the choice between kitting and line stocking, and present a rich array of research opportunities in a number of relevant areas.     

Use of activity-based costing and economic value analysis for the justification of capital investments in automated material handling systems

This paper develops a two-stage method for the justification of investment in modern material handling systems. The underlying approach places heavy emphasis on the use of cost avoidance data quantified by activity-based costing systems. The first stage collects the life-cycle costs and benefits resulting from the reconfiguration of material handling systems in manufacturing facilities. A recently developed software package for process modelling and management is employed to capture the characteristics of material handling activities and to derive accurate applied cost rates for each activity and material handling system combination. These activity-related cost data as well as various opportunity costs are incorporated in a case-specific, investment decision model that constitutes the second stage of the method. The model performs an Economic Value Analysis for each material handling alternative. In doing so, it offers a sound basis for economic comparison of different systems. A case study illustrates the merit of our two-stage method in decision making by placing an accurate and reliable economic value on the transition from manual to automated material handling in a manufacturing facility. The use of activity-based costs reverses the decision of sustaining the 'status quo' supported by a traditional investment justification approach restricted to solely labour cost reductions     

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.     

The effects of work-in-process inventory costs on the design and scheduling of assembly lines with low throughput and high component costs

This paper considers a class of assembly systems with long cycle times (low volume of output) and highly expensive components or subassemblies. Systems such as these are typical for companies in the aerospace industry assembling missiles and airplanes. As each unit of the product moves along the assembly line, its value increases owing to additional parts or components installed and the additional work performed. We show that sequencing activities according to ascending values of the ratios of the 'value added' to activity duration minimizes inventory holding cost within a given workstation. A branch-and-bound procedure is then used to allocate activities optimally to a given number of workstations. The objective function used in this paper is to maximize the net profit of a production line, which comprises net revenues minus inventory holding costs and fixed costs of workstations. The design of the assembly line is affected by two decision variables: number of workstations and cycle time. Finally, it is shown that a 'balanced' line is not necessarily an optimal one and 'pushing' activities to the right (the end of the assembly line) may reduce total holding costs and improve the profitability of the line.     

DFT的装配车间生产物流策略仿真与研究

针对某汽车部件的实际装配生产,运用离散事件仿真的方法对基于需求流动技术(DFT)的装配生产物流策略进行了研究.在分析该汽车部件装配生产流程的基础上,确定eM-Plant仿真软件中的建模对象与装配生产系统中实体对象的对应关系,使用面向对象的方法建立了相应的离散事件仿真模型.在模型中分别实施基于推式生产方式的物流策略和基于DFT的物流策略,以该汽车部件的平均日产量为绩效指标,比较了两种物流策略对装配生产的影响.     

Optimising part feeding in the automotive assembly industry: deciding between kitting and line stocking

In a synchronous and fast-paced assembly line operation, it is crucial that the right parts are being supplied at the right time and at the right place. In automotive assembly, the need for efficient material handling part delivery is particularly great because of extensive product customisation and the lack of space to stock all the required parts at the assembly line. This paper introduces a mathematical cost model for evaluating the assignment of parts to one of two possible material supply systems: kitting or line stocking. Case data from an automotive company in Belgium is used to test the model. The results demonstrate that hybrid policies, where some parts will be kitted while others will be stocked in bulk at the line, are preferred to the exclusive use of either material delivery system. The factors influencing the preferred delivery method for individual parts are explored. Numerical results are presented.     

Design of stochastic assembly lines considering line balancing and part feeding with supermarkets

This article aims to address the assembly line balancing problem (ALBP) and supermarket location problem (SLP) as two long-term interrelated decision problems considering the stochastic nature of the task times and demands. These problems arise in real-world assembly lines during the strategic decision-making phase of configuring new assembly lines from both line balancing and part-feeding (PF) aspects. A hierarchical mathematical programming model is developed, in which the first level resolves the stochastic ALBP by minimizing the workstation numbers and the second level deals with the stochastic SLP while optimizing the PF shipment, inventory and installation costs. The results of case data from an automotive parts manufacturer and a set of standard test problems verified that the proposed model can optimize the configuration of assembly lines considering both ALBP and SLP performance measures. This study also validates the effect of the stochastic ALBP on the resulting SLP solutions.     

An efficient hybrid meta-heuristic for a cross-docking system with temporary storage

Cross-docking is a distribution system where products arriving at the warehouse (distribution centre) are organised, loaded and shipped for delivery to customers without storage and picking. Arrival is performed by inbound trucks, having products verified and organised at the receiving docks according to their destinations and customer demand. These products are directly sent to shipping dock and loaded in outbound trucks which will make deliveries to customers. Thus, inventory costs and delivery times to customers are reduced. An important parameter for successful implementation of cross-docking is the efficiency related to the scheduling of inbound and outbound trucks, as well as the transfer of products. This research presents a hybrid genetic algorithm with tabu search to find good scheduling of trucks, reducing total operating time. A meta-heuristic was tested on instances and solutions reveal themselves as equal as or better than those of literature.     

Cellular machine layout based on the Segmented Flow Topology

This paper introduces a facility layout design procedure for converting an existing manufacturing system with a predefined aisle structure to a cellular manufacturing system based on the 'segmented flow topology' (SFT) developed by Sinriech and Tanchoco. The proposed procedure is aimed at finding the best machine grouping, along with the locations of pick-up and delivery stations and machine layout for each cell based on an existing facility. The objective is to minimize the total material handling cost. In contrast to previous work in this area, the proposed design procedure takes into account both distance and material flow in forming machine clusters. In addition, a revised cost model for material handling system, which accounts for different aspects of capital and operating cost, is presented.     

Sequencing mixed-model assembly lines to minimize part inventory cost

A mixed-model assembly line enables the joint production of different models of a common base product in intermixed model sequence (lot size one). Previous approaches for the short-term planning task of model sequencing either aim at minimizing work overload (mixed-model sequencing and car sequencing) or leveling part usages (level scheduling). However, at many manufacturers parts are consolidated by a third party logistics provider, who stocks Just-in-Time delivered parts in a consignment warehouse adjacent to the line. The manufacturer issues a complete cargo carrier (e.g. a euro-pallet) whenever his own intermediate storage of parts is depleted. Thus, the manufacturer aims at a model sequence which minimizes his own inventory costs. This paper formalizes this novel model sequencing problem and describes different heuristic and exact procedures. Furthermore, the solutions yielded by these approaches are compared to the traditional level scheduling.     

Fuzzy approach to the robust facility layout in uncertain production environments

The proposed method approaches the problem of the optimal facility layout using fuzzy theory. The optimal layout is a robust layout that minimizes the total material handling cost, when the product market demands are uncertain variables, which are defined as fuzzy numbers. Since each department has a limited production capacity, not all possible combinations, deriving from each product's market demand, are taken into account because some combination could exceed the overall department's productivity. Therefore, the optimal solution results by solving a 'constrained' fuzzy optimization problem, in which the fuzzy material handling costs corresponding to the layouts are evaluated, and a ranking method, which considers the grade of pessimism of the decision maker, is established to determine the optimal layout.     

An interactive approach to computer aided facility layout

In all manufacturing and service industries the layout of facilities is an important determinant of operating efficiency and costs. Whenever the flow of materials or people is complex, computerized procedures offer the only feasible means of developing and evaluating alternative arrangements.

This paper describes an interactive approach to construction and improvement procedures which utilizes a refresh graphics terminal (IMLAC)linked to a PRIME 400 computer. Input includes projected materials flow, estimates of material handling costs, 2-D templates of machines, etc., and an initial layout which can be either existing, proposed, or constructed using the procedure INLAYT. A heuristic procedure, S-ZAKY, utilizes multi-pairwise facility exchange to develop improved layouts based upon an analysis of materials flow. The improved layout is displayed in detail alongside the initial layout at the graphics terminal together with relevant material handling costs. The user may then accept, reject or modify the improved layout using the light-pen attached to the terminal before proceeding to successive iterations until satisfied. An economic evaluation of the projected savings in material handling costs against costs of relayout may be displayed at each iteration. On completion, a fully documented record including drawings may be obtained for every stage in the. procedure.     

A genetic algorithm and queuing theory based methodology for facilities layout problem

Facilities layout, being a significant contributor to manufacturing performance, has been studied many times over the past few decades. Existing studies are mainly based on material handling cost and have neglected several critical variations inherent in a manufacturing system. The static nature of available models has reduced the quality of the estimates of performance and led to not achieving an optimal layout. Using a queuing network model, an established tool to quantify the variations of a system and operational performance factors including work-in-process (WIP) and utilisation, can significantly help decision makers in solving a facilities layout problem. The queuing model utilised in this paper is our extension to the existing models through incorporating concurrently several operational features: availability of raw material, alternate routing of parts, effectiveness of a maintenance facility, quality of products, availability of processing tools and material handling equipment. On the other hand, a queuing model is not an optimisation tool in itself. A genetic algorithm, an effective search process for exploring a large search space, has been selected and implemented to solve the layout problem modelled with queuing theory. This combination provides a unique opportunity to consider the stochastic variations while achieving a good layout. A layout problem with unequal area facilities is considered in this paper. A good layout solution is the one which minimises the following four parameters: WIP cost, material handling cost, deviation cost, and relocation cost. Observations from experimental analysis are also reported in this paper. Our proposed methodology demonstrates that it has a potential to integrate several related decision-making problems in a unified framework.