Machine Layout Research Articles

CNC Planing Process for Turbine Twisted Blade Profile

In this paper, a multi-axis follow-up CNC planing process for twisted blade profile is proposed to reduce the machining cost and achieve high machining efficiency. Firstly, the planing process of the turbine twisted blade is analysed to determine the planing shaping movements; then the machine layout and CNC planing system needed to realize the shaping movements are constructed; then the implementation method of the multi-axis follow-up function which is unique to the CNC planing system is studied; Finally, a proof experiment of this machining process has been done to verify its feasibility.

Rancangan Tata Letak Fasilitas Produksi Produk Rehabilitasi Dengan Algoritma Genetika

The layout of production facilities has a very important impact and interrelationship between facilities with each other to support the smoothness of the production process.Frequently the biggest problems in the production system are caused by unsystematic handling of materials. This study, applies a genetic algorithm to obtain a facility layout design (machine) optimally. Inputs from this study include machine numbers, machine dimensions, machine sequences in each section, production volume in each section, and flow frequency in each section. The output of this study is the machine layout with a minimum total flow cost. This study solved the case in the rehab product production facility at PT Shima Prima Utama which consisting of 16 machines and 29 components. The results of the study in this case are that the optimal machine placement sequence is 13, 3, 9, 15, 6, 10, 2, 12, 8, 16, 7, 1, 11, 5, 14 and 4 with a total flow cost of 197,434.

Robust machine layout design under dynamic environment: Dynamic customer demand and machine maintenance

The layout of manufacturing facilities has a large impact on manufacturing performance. The layout design process produces a block plan that shows the relative positioning of resources that can be developed into a detailed layout drawing. The total material handling distance is commonly used for measuring material flow. Manufacturing systems are subject to external and internal uncertainties including demand and machine breakdowns. Uncertainty and the rerouting of material flows have an impact on the material handling distance. No previous research has integrated robust machine layout design through multiple periods of dynamic demand with machine maintenance planning. This paper presents a robust machine layout design tool that minimises the material flow distance using a Genetic Algorithm (GA), taking into account demand uncertainty and machine maintenance. Experiments were conducted using eleven benchmark datasets that considered three scenarios: preventive maintenance (PM), corrective maintenance (CM) and both PM and CM. The results were analysed statistically. The effect of several maintenance scenarios including the ratio of the number of machines with period-based PM (PPM) to the number with production quantity-based PM (QPM), the percentage of machines with CM (%CM), and a combination of PMM/QPM ratios and %CM on material flow distance were examined. The results show that designing robust layouts considering maintenance resulted in shorter material flow distances. The distance was decreased by 30.91%, 9.8%, and 20.7% for the PM, CM, and both PM/CM scenarios, respectively. The PPM/QPM ratios, %CM, and a combination of PPM/QPM and %CM had significantly resulted in the material flow distance on almost all datasets.

Heuristic and meta-heuristic algorithms for solving medium and large scale sized cellular manufacturing system NP-hard problems: A comprehensive review

Abstract Shorter cellular manufacturing systems (CMSs) have emerged to cope with such production requirements and have been implemented with favourable results. Designing and implementing effective CMS involves many problems such as cell formation, machine layout, alternative process routes and inventory lot sizing. To review different heuristic, meta-heuristic, hybrid and exact solution algorithms developed to solve NP-hard problems associated with medium and large sized CMS problems. However, most of the researchers mainly focus on single optimization problem as multi-optimization results in poor performance. Hence, a robust meta-heuristic algorithm with hybridization is essential to address multiple CMS problems simultaneously.

Machine Layout Decision Algorithm for Cell Formation Problem Using Self-Organizing Map

Self Organizing Map (SOM) is a neural network that is effective in classifying patterns that form the feature map by extracting characteristics of the input data. In this study, we propose an algorithm to determine the cell formation and the machine layout within the cell for the cell formation problem with operation sequence using the SOM. In the proposed algorithm, the output layer of the SOM is a one-dimensional structure, and the SOM is applied to the parts and the machine in two steps. The initial cell is formed when the formed clusters is grouped largely by the utilization of the machine within the cell. At this stage, machine cell are formed. The next step is to create a flow matrix of the all machine that calculates the frequency of consecutive forward movement for the machine. The machine layout order in each machine cell is determined based on this flow matrix so that the machine operation sequence is most reflected. The final step is to optimize the overall machine and parts to increase machine layout efficiency. As a result, the final cell is formed and the machine layout within the cell is determined. The proposed algorithm was tested on well-known cell formation problems with operation sequence shown in previous papers. The proposed algorithm has better performance than the other algorithms.

Machine layout design problem under product family evolution in reconfigurable manufacturing environment: a two-phase-based AMOSA approach

Reconfigurable manufacturing systems (RMSs) are designed to manufacture a specific product, incorporating the scalability to other products in the same family. This ability is based primarily on the reconfiguration capabilities offered by reconfigurable machines tools (RMTs). This paper addresses one of the most important aspects related to the reactivity of RMSs. More specifically, it considers the relations, which link the conceived system with two important environments: its logical environment, i.e., the product family (products that share similarities) in which the RMS can evolve, and its physical environment, i.e., the physical workshop that implements this RMS. We study the machine layout problem by considering the product family evolution where two sub-problems are addressed. The first sub-problem concerns the evolution of the product, in the same family, towards new products to meet the evolutions and the requirements of the customers. The second sub-problem deals with the machine layout problem based on the results of the first sub-problem. For this, our two-phase-based approach combines the well-known metaheuristic, archived multi-objective simulated annealing (AMOSA), with an exhaustive search–based heuristic to determine the best machine layout for all the selected machines of the product family. The developed approach is based on the initially generated process plans of products (in the product family) for the RMS design under performance metrics. Moreover, the proposed layout must, at its best, respect both the constraints imposed by the generated process plans and those depicting the available location in the shop floor where machines can be placed. An illustrative numerical example is proposed to demonstrate the applicability of our approach.

A novel approach to determine the cell formation using heuristics approach

Cellular manufacturing is a vital part of lean manufacturing. It is an application of group technology. Three problems in cellular manufacturing are cell formation, machine layout and cell layout problems. However, these problems are NP-hard optimisation problems and cannot be solved using exact methods. A difficult part is to form the machine groups or cells, also called Cell Formation Problem and several techniques have been proposed to solve the same. In this paper, the Cell Formation Problem is solved using an integrated approach of heuristics along with Genetic Algorithm and Membership Index. Heuristics technique is used for domain selection which is used in Genetic Algorithm as the initial population. Genetic Algorithm is useful for optimising the results of machine assignment to cells, and Membership Index is used to assign parts to the cells. The performance is analysed using performance measures such as group technology efficiency and some exceptional elements. The proposed computational methodology is tested on standard problems of diverse size from literature papers using the hybrid approach. Results from test problems show that the proposed method is effective and efficient. The paper is useful from the practicality aspect and also relevant from current research and industry trends.

Efficiency of Different Machine Layouts for Chain Flail Delimbing, Debarking and Chipping

Based on data collected from seven commercial harvesting operations in Western Australia, the study developed a productivity model for chain flail delimber–debarker–chippers (CFDDCs) used in blue gum (Eucalyptus globulus Labill.) plantations. The tests covered 45 h and 3395 cycles, and were conducted using time-study techniques. Despite the observational character of the study and the dampening effect of multi-tree processing, the study yielded a viable prediction model for estimating CFDDC productivity as a function of mean tree size, tree form, bark–wood bond strength (BWBS), and machine type. Productivity increased with mean tree size on a logarithmic scale, and was lower for poorly formed trees and high BWBS. Under equal conditions, a separate delimber–debarker and a chipper were 10% to 20% less productive than the integrated delimber–debarker–chipper. Productivity estimates were consistent with those reported in published case studies of CFDDCs used in planted Eucalyptus. Neither this study nor any of the previous ones could offer a reliable estimate of long-term machine utilization, which would be an ideal subject for future research.

An integrated approach for solving cell formation and intra cell machine layout problem considering operation sequence and alternative process routing.

Cellular manufacturing is a group technology approach wherein parts and machines are arranged in flow production. Most of the cell formation methods in the previous literature have addressed the zero-one matrix for solving cell formation problem with single process routing. Even though multiple routings are considered in some cases, machine layout is not considered which results in increased number of backward flow, voids and exceptional elements. In this research, we have proposed a new heuristic approach for solving cell formation problem based on new similarity coefficient method and identifying intra-cell machine layout based on flow matrix by considering operation sequence and alternative routings. In order to validate the efficiency of our proposed method, five well-known test problems from the literature are employed and the results are compared with the existing method the results clearly show that the proposed approach which that provides superior or equal solution than the existing method.

A New Hybrid Approach for Machine Layout Design Under Family Product Evolution for Reconfigurable Manufacturing Systems

Reconfigurable manufacturing system (RMS) is a new paradigm that answers many of the challenges that the market nowadays imposes. In this paper, we address one of the most important aspects related to the reactivity of RMSs. We consider the relations, which link the conceived system with two important environments: its logical environment, i.e., the product family in which the RMS can evolve, and its physical environment, i.e., the physical workshop that implements this RMS. More specifically, we study the machine layout problem by considering the family product evolution where two sub-problems are considered. The first sub-problem concerns the evolution of the product, in the same family, towards new products to meet the evolutions and the requirements of the customers. The second sub-problem deals with the machine layout problem based on the results of the first sub-problem. We develop an approach which combines the well-known metaheuristic, archived multi-objective simulated annealing (AMOSA), with an exhaustive search-based heuristic to determine the best machine layout for all the selected machines of our product family. The approach is based on the initially generated process plans of products (in the product family) for the RMS design under performance metrics. The proposed layout must at its best, respects both the constraints imposed by the generated process plans and those depicting the available location in the shop floor where machines can be placed. To show the applicability of our approach, we present a simple numerical example and discuss the obtained numerical results.

A dynamic multiobjective model for designing machine layouts

This study proposes a model for (re-)designing machine layouts in already existing facilities with a multi-period time planning horizon. The model can be applied in several situations and at different moments of a layout life cycle, for example to design the initial layout of an existing facility, or to make some specific and local reconfigurations. This dynamic multiobjective model minimizes costs (production, material handling and reconfiguration costs), maximizes adjacency between machines, minimizes unsuitability (to combine characteristics of the machines and of the existing locations), and can allow changes between periods on the product mix or on the machine layout requirements (e.g., required area). The performance of the model was tested with a case study based on a real first-tier supplier of the automotive industry, thus showing the practical potential of the proposed approach.

A Three-Stage Approach to a Multirow Parallel Machine Layout Problem

Facility layout is vital to save operational cost and enhance production efficiency. Multirow layout is a common pattern in practical manufacturing environment. Although parallel machines are frequently implemented in practice to enhance productivity, there lacks any in-depth study on multirow layout problem with parallel machines. In this paper, its mathematical programming formulation is established to minimize material flow cost. A three-stage approach is proposed to solve it. First, a Monte Carlo heuristic is devised to optimize the sequence of machines on multiple rows. Second, a linear program is used to determine the optimal exact location of each machine. Finally, an exchange heuristic is adopted to reassign material flows among parallel machines in different machine groups. An iterative optimization strategy is suggested to execute the three stages repeatedly to improve the solution quality. This approach is applied to a number of problem instances and compared against others. The experimental results show that it is able to effectively solve this new problem and significantly decrease material flow cost. Note to Practitioners —Multirow layout is common in practical manufacturing systems in which parallel machines are often used to improve productivity, shorten production time, and guarantee some flexibility. This paper studies a multirow parallel machine layout problem that involves machine groups, each of which contains parallel machines. Solving it is to locate all machines at multiple parallel rows to minimize material flow cost. It is challenging because one needs to decompose material flows and determine exact locations of machines simultaneously. A three-stage approach is proposed to do so. It is applied to many problem instances. The results demonstrate that it works well for such layout problems with parallel machines.

Comparison of Two Transverse Flux Machines for an Aerospace Application

More electric is a platform being widely adopted by the current generation of aircraft. It offers significant benefits in terms of fuel savings and flexibility of airframe design but relies on the development of torque dense machines. This paper documents the development of an air-cooled transverse flux machine for use in short-haul aircraft to improve on-ground operational efficiency. If its potential is to be realized, this topology of the machine comes with a new set of manufacturing challenges. Two competing machine layouts with different approaches toward their fabrication are discussed. Experimental results and experiences gained from overcoming the challenges of building the machines are presented. A combined phase topology with soft magnetic composite core-back is shown to give a better rated torque, whereas a separate phase bent lamination concept gives better overload capability.

Induced activation studies for the LHC upgrade to High Luminosity LHC

The Large Hadron Collider (LHC) will be upgraded in 2019/2020 to increase its luminosity (rate of collisions) by a factor of five beyond its design value and the integrated luminosity by a factor ten, in order to maintain scientific progress and exploit its full capacity. The novel machine configuration, called High Luminosity LHC (HL-LHC), will increase consequently the level of activation of its components. The evaluation of the radiological impact of the HL-LHC operation in the Long Straight Sections of the Insertion Region 1 (ATLAS) and Insertion Region 5 (CMS) is presented. Using the Monte Carlo code FLUKA, ambient dose equivalent rate estimations have been performed on the basis of two announced operating scenarios and using the latest available machine layout. The HL-LHC project requires new technical infrastructure with caverns and 300 m long tunnels along the Insertion Regions 1 and 5. The new underground service galleries will be accessible during the operation of the accelerator machine. The radiological risk assessment for the Civil Engineering work foreseen to start excavating the new galleries in the next LHC Long Shutdown and the radiological impact of the machine operation will be discussed.

Design and Optimization of Fuel Injection of a 50 kW Micro Turbogas

The present article deals with the design of a micro turbogas turbine suitable for on board applications, e.g., as a power generator on hybrid transit bus, characterized by a simple constructive approach. Deriving the machine layout from an existing KJ-66 aircraft model engine, the authors propose a theoretical design of a compact, lightweight turbogas turbine, by investigating the technical possibility and limits of the proposed design. In particular, a different combustion chamber layout has been proposed, and fuel adduction channels for different swirler designs have been simulated via ANSYS Fluent in order to identify a satisfactory fuel spreading. As a result, the complete characterization of the design parameters and geometries has been performed, and a series of RANS simulations has been used in order to identify an optimal swirler configuration.

A mixed-integer programming formulation for the double row layout of machines in manufacturing systems

The Double Row Layout Problem (DRLP) is the problem of allocating a given set of machines on both sides of a straight line corridor so as to minimise the total cost of transporting materials among machines. The DRLP occurs in several manufacturing plants, particularly in semiconductor manufacturing. While it has a large practical importance, the problem is very difficult to solve to optimality. In this paper, we construct a mixed-integer programming (MIP) formulation of the problem, which favourably compares to a previously published MIP formulation. The new model is found to present similar performance to another published MIP formulation, and it has the advantage of being more intuitive for handling qualitative inputs that may be required in a layout refinement phase.

Investigation of Effect of Machine Layout on Productivity and Utilization Level: What If Simulation Approach

Designing and selecting the material handling system is a vital factor for any production line, and as result for the whole manufacturing system. Poor design and unsuitable handling equipment may increase the risk of having bottlenecks, longer production time and as a result the higher total production cost. One of the useful and effective tools are using “what if” simulation techniques. However, this technique needs effective simulation software. The main objective for this research is to simulate different types of handling system using what if scenario. To achieve the objective of the research, Delmia Quest software has been used to simulate two different systems: manual system and conveyers system for the same production line and analyses the differences in terms of utilization and production rate. The results obtained have been analysed and appraised to induce the bottleneck locations, productivity and utilizations of the machines and material handling systems used in the design system. Finally, the best model have been developed to increase the productivity, utilizations of the machines, material handling systems and to minimize the bottleneck locations.

EUPRAXIA@SPARC_LAB: Beam dynamics studies for the X-band Linac

In the framework of the Eupraxia Design Study an advanced accelerator facility EUPRAXIA@SPARC_LAB has been proposed to be realized at Frascati (Italy) Laboratories of INFN. Two advanced acceleration schemes will be applied, namely an ultimate high gradient 1 GeV X-band linac together with a plasma acceleration stage to provide accelerating gradients of the GeV/m order. A FEL scheme is foreseen to produce X-ray beams within 3-10 nm range. A 500-TW Laser system is also foreseen for electron and ion production experiments and a Compton backscattering Interaction is planned together with extraction beamlines at intermediate electron beam energy for neutron beams and THz radiation production. The electron beam dynamics studies in the linac are here presented together with the preliminary machine layout.

Performance improvement of Teaching-Learning-Based Optimisation for robust machine layout design

Teaching-Learning-Based Optimisation (TLBO) is one of the more recently developed metaheuristics and has been successfully applied to solve various optimisation problems. However, TLBO has not been academically reported for solving the robust machine layout design (MLD) problems with dynamic demand. Considering internal logistics activities, shortening material flow distance within a manufacturing area can lead to efficient productivity and a decrease in related costs. The robust machine layout is concerned with determining the efficient arrangement of machines/facilities located on a manufacturing shop floor under future demand fluctuation. A robust designed layout is essential for a company to maintain a high productivity rate through multiple time-periods of demand uncertainty with minimum effects related to the re-layout time and cost, manufacturing disruption, and the movement of monument machines. The objectives of this paper were to: i) describe the development of a computer aided layout designing tool for minimising the total material flow distance under dynamic demand scenario, ii) investigate the appropriate setting of TLBO parameters, and iii) propose four TLBO modifications for improving its performance. The modified TLBOs were inspired by multiple teachers with two types of classes and two approaches to teacher selection. The numerical experiments were designed and conducted using eleven MLD benchmarking datasets. Statistical analyses on the experimental results showed a superior performance for the proposed modifications.

A memetic algorithm for the generalised machine layout problem

Designing efficient machine layouts is a key issue to ensure profitability in manufacturing environments. The major decisions in designing machine layouts are: the selection of machines (including machine replicas); the assigning of machines to the plant floor; the selection of production mix (i.e., determine the products to be produced); and the assigning of products to machines (i.e., determining the product flows). The generalised machine layout problem (GMALP) integrates these factors under a single problem. The contribution of this paper is the development of a memetic algorithm for the GMALP. The memetic algorithm takes advantage of the diversification strategies of the genetic algorithm combined with the intensification strategies of tabu search. Results obtained with the memetic algorithm compares favourably with the results presented in the literature.