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.     

A Material Handling System Selection Model

A technique is presented which can be used to design, or assist in the design of, an integrated materials handling system for a manufacturing facility or a major department of the facility. The developed procedure selects the materials handling equipment to be used to perform a given set of moves in order to miriimize the system's costs associated with the handling, assuming the plant arrangement remains fixed. To demonstrate the selection procedure, an example problem is presented. Since the method is heuristic, no claim of optimality is made.     

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     

Unequal-area,fixed-shape facility layout problems using the firefly algorithm

In manufacturing industries, the facility layout design is a very important task, as it is concerned with the overall manufacturing cost and profit of the industry. The facility layout problem (FLP) is solved by arranging the departments or facilities of known dimensions on the available floor space. The objective of this article is to implement the firefly algorithm (FA) for solving unequal-area, fixed-shape FLPs and optimizing the costs of total material handling and transportation between the facilities. The FA is a nature-inspired algorithm and can be used for combinatorial optimization problems. Benchmark problems from the previous literature are solved using the FA. To check its effectiveness, it is implemented to solve large-sized FLPs. Computational results obtained using the FA show that the algorithm is less time consuming and the total layout costs for FLPs are better than the best results achieved so far.     

ADVISOR: A computer-aided material handling equipment selection system

This paper develops and describes a systematic computer-assisted methodology for the selection of material handling equipment (MHE). A microcomputer based system called ADVISOR models the material handling equipment selection process and employs information on 77 of the most common equipment types used in material transport, positioning, unit formation, and storage. The system identifies the appropriate equipment type for an application in two stages. At the primary stage, potential equipment types are identified through the use of physical requirements of the material handling activities specified by users. Eligible equipment are ranked according to their normalized accumulated rating and placed in a candidate equipment list. After this, a second stage involving an economic analysis for each eligible equipment is performed. The evaluation criteria provided by ADVISOR include present worth (PW).equivalent uniform annual cost (EUAC), return on investment (ROI), and payback period(PP) methods. Through ADVISOR, the expert-like MHE selection system recommends a ranked set of equipment based on user input data. An example problem is given in the paper to demonstrate the use of the system.     

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。     

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.     

MULTI-HOPE: A tool for multiple floor layout problems

The objective of most facility layout problems is to minimize material handling cost, which is directly proportional to both the distance between the machines and the mix, as well as the volume of products handled. The mix and volume of products are dependent on the demand patterns, and the distance is dependent on the layout plan used for the facility. Because it is relatively difficult to change the demand patterns, and hence the mix and volume of products, the primary focus of most designers has been to deal with the distance attribute of the material handling costs. The limitations of available horizontal space create a need to explore vertical expansion of facilities. This brings up new aspects of vertical material handling and flow that need to be considered in the facility design problem. In this paper, we present a genetic algorithm-based heuristic for generating block layouts for multiple-floor layout problems. This approach produces better solutions than existing simulated annealing-based heuristics for all but one of five multiplefloor test problems available in the literature.     

Facility layout design in a changing environment

Increasing global competition, rapid changes in technology and the necessity to respond quickly to a cost and quality conscious customer have changed the dynamics of facilities planning. Today's manufacturing facility needs to be responsive to the frequent changes in product mix and demand while minimizing material handling and machine relocation costs. In this paper, we present a framework for the design of a dynamic facility which can respond effectively to the changes in product design, mix and volume in a continuously evolving work environment. A genetic algorithm-based heuristic is used for solving the design problem and two test cases are presented to illustrate the use of the methodology.     

Effective material flow at an assembly facility

Effective material flow in an assembly facility leads to reduced material handling costs and increased productivity. This research focuses on improving the flow of materials for an assembly facility that receives supplied parts through receiving docks and transfers the parts to material storage locations and then to part usage locations. The locations of the receiving docks, storage locations, and line locations are predetermined, but the assignment of parts to dock locations and storage locations and the material flow paths through the facility are decision variables. Furthermore, design decisions such as the dock strategy employed and the configuration of the storage areas lead to additional decision variables. The goal is to reduce overall material handling costs by effectively receiving, storing and transferring the material from loading docks to line locations. The contribution of this research is in applying multi-commodity network flow models that integrate many of the sub-problems that are assumed to be solved a priori in many existing models. This integrated approach was used to evaluate configuration changes for a collaborating facility. One of the scenarios analysed showed an improvement in the material handling costs of nearly 10% as compared to current practices.     

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).     

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.     

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     

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.     

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.     

An applied model for the facilities design problem

A model ia described which can be used to assist in the design of a facility, where the facilities design includes the selection of the materials handling system and the placement of departments within the facility. The model is entitled COFAD, an acronym representing Computerized FAcilities Design. COFAD selects the facilities design which approaches the minimal materials handling system cost. The input requirements and the utilization of COFAD are demonstrated via an example problem. Although it is shown that the model results in good solutions, due to the complexity of the design problem, no claim of optimality can be made.     

Modelling of three-dimensional warehouse systems

The objective of this research is the development of an optimization procedure to aid a warehouse planner in the design of selected three-dimensional, palletized storage systems. All alternatives are compared in the overall model while simultaneously considered the following factors: control procedures, handling equipment movement in an aisle, storage rules, alternative handling equipment, input and output patterns for product flow, storage rack structure, component costs and the economics of each storage system. The resultant model is more complete than any other currently available for use by a designer in this complex decision environment.     

Incorporating heterogeneous distance metrics within block layout design

This paper focuses on optimal design of block layouts when using more than one distance metric within a single facility. Previous work in block layout has assumed a single distance metric, usually the shortest rectilinear distance between department centroids, during the design step. However, most facilities have more than one method of material handling and alternative material handling systems can imply alternative distance metrics and cost structures. Specifically, up to three distance metrics within a single facility are considered--the shortest rectilinear distance between centroids (appropriate for automated guided vehicles and forklift trucks), the Tchebychev (maximum) distance (appropriate for overhead cranes) and the shortest Euclidean distance between centroids (appropriate for conveyor lines). Optimal block layouts using each of these distance metrics individually and then collectively are compared and contrasted. This approach can also be used to compare layouts when the choice of material handling system is not clear. It is argued that incorporating the distance metric that best reflects the planned material handling device is more realistic than previous formulations, avoids block layouts that are sub-optimal for the material handling systems installed, and is quite workable within a heuristic optimization framework.     

An integrated methodology for automating the determination of layout and materials handling system

There is a severe scanty of models and solution techniques for the determination of layout and the materials handling system when neither are fixed. This is a complex problem for which this paper proposes a new integrated methodology using a knowledge-based/optimisation approach to the problem. The knowledge-base consists of facts and rules to determine the feasibility of using a materials handling equipment type for a given move. The optimisation part determines the layout of machines minimising the materials handling costs and the dead space in the layout using a multi-criteria optimisation model. The methodology aims to minimise materials handling costs, aisle space usage and dead-space in the resulting layout. It is particularly applicable to heavy manufacturing environments. The system outputs the optimum location, configuration and orientation of machines, and the material handling equipment types, their design capacities, utilisations and the assignment of moves to each item of materials handling equipment. The results of a successful application to an example problem are given.     

A robust cell formation approach for varying product demands

In cellular manufacturing environments, manufacturing cells are generally formed based on deterministic product demands. In this paper, we consider a system configuration problem with product demands expressed in a number of probabilistic scenarios. An optimization model integrating cell formation and part allocation is developed to generate a robust system configuration to minimize machine cost and expected inter-cell material handling cost. A two-stage Tabu search based heuristic algorithm is developed to find the optimal or near optimal solutions to the NP-hard problem. Numerical examples show that this model leads to an appropriate compromise between system configuration costs and expected material handling costs to meet the varying product demands. These example problems also show that the proposed algorithm is effective and computationally efficient for small or medium size problems.