Flexible Machine Research Articles

Two-machine flow shop scheduling problem with blocking, multi-task flexibility of the first machine, and preemption

Blocking flow shop scheduling problem has been extensively studied in recent years; however, some applications mentioned for this problem have some additional characteristics that have not been well considered. Multi-task flexibility of machines and preemption are two of such characteristics. Multi-task flexible machines are capable of processing the operations of at least one other machine in the system. In addition, if preemption is allowed, the solution space grows, and solutions that are more efficient may be obtained. In this study, the two-machine flow shop scheduling problem with blocking, multi-task flexibility of the first machine, and preemption is investigated by considering the minimization of makespan as criterion. It is proved that the complexity of the problem is strongly NP-hard. Because of preemption and multi-task flexibility, there are infinite schedules for each sequence; however, it is shown that a dominant schedule can be defined for each sequence. Two mathematical models are proposed for optimally solving the small-sized instances. Furthermore, a variable neighborhood search algorithm (VNS) and a new variant of it, namely, dynamic VNS (DVNS), are presented to find high quality solutions for large-sized instances. Unlike the VNS algorithm, the DVNS algorithm does not need tuning for the shaking phase. Nevertheless, computational results show that DVNS has even a slightly better performance. The VNS and DVNS algorithms are also compared with some of the best-performing metaheuristics already developed for the flow shop scheduling problem with blocking and minimization of makespan as criterion. Computational results reveal that both algorithms are superior to the others for large-sized instances.

Processing Single Crystal SiC with Semi-Consolidated Polishing Film

Single crystal SiC has been considered as a leading wide band gap semiconductor for its excellent properties even in severe environments. While the outstanding chemical and mechanical inertness also makes it a difficult to process material. In this work, a flexible machining method was proposed to polish 6H-SiC wafers with semi-consolidated diamond tools prepared by sol-gel technology. To confirm the machining mechanism of this newly developed method, free abrasive polishing slurry and fixed abrasive lapping film were also used for comparative experiments. The results indicated that high quality wafer surface with roughness of Ra 0.962 nm was achieved by using semi-consolidated polishing film with diamond grit size of 1 μm. And compared to the other two machining methods, the abrasive in this flexible tool would take a retraction when polishing, leading to a smoother and scratch-free surface of the work piece.

Investigation on Effects of Alternative Process Routing in the Design of Cellular Manufacturing System

Background/Objectives: The adoption of cellular manufacturing becomes promising manufacturing philosophy to address the problems of today’s manufacturing plants such as an increasingly turbulent environment and rising customer requirements. Method/Statistical Analysis: Group Technology and Cellular Manufacturing System (CMS) have together paved way for the same through processing of similar parts groups as part families and the formation of a machine cell dedicated for the manufacture of the part family. The traditional CMS design methods do not incorporate many real-life manufacturing parameters such as batch size and machine flexibility, various cost factors at the design stage and also they are not taking the advantage of the machine flexibility in terms of coexistence of alternate process routing. Findings: In this work, a comprehensive mathematical model has been developed capturing these exact production parameters. An optimal solution is obtained using Lingo 8.0 software package and a solution methodology of best possible cell configurations is formed. Applications/Improvements: The effect of considering the alternate process routing in the design stage of CMS is evaluated and it is found that routing flexibility results in better cell configurations.

A Resource Reservation based Framework for QoS-aware Resource Provision in Cloud Computing

Recently, service of quality (QoS) of cloud platform has attracted more and more attentions as plenty of commercial clouds are deployed in real world. However, providing desirable QoS for end-users still remains a challenging problem because of the unpredictable workload in cloud platforms. In this paper, we present a novel QoS framework called QVRP, which enables us to enhance user’s QoS satisfactory through a flexible virtual machine reservation mechanism. The implementation of QVRP is implemented as an integrated middleware that makes it easy to be incorporated in many cloud platforms. Extensive experiments are conducted to examine the effectiveness and performance of QVRP, and the results indicate that it can significantly improve many important QoS metrics, which in turn improves the cloud user’s QoS satisfactory.

Offline simulation of path deviation due to joint compliance and hysteresis for robot machining

Industrial robots offer a cost-effective and flexible machining alternative to the classic machining centers. One disadvantage is the significantly reduced working accuracy that results in considerable path deviation, particularly under load. To maximize the effectiveness of the robot and to derive suitable machining strategies, knowledge of the effects on the working accuracy is required. In this study, a model is presented in joint space that predicts the path deviation on the basis of joint stiffness and reversal error with high accuracy, with respect to the kinematic model and path planning. The identification of the model parameters of individual joints is carried out without disassembling the robot. The model is validated against the hysteresis occurring at the Tool Center Point and through the milling of circular contours. It is shown that the reversal error is mainly caused by hysteresis and not by backlash at zero crossing. The subsequent offline compensation strategy allows a considerable reduction of dimension and form deviations.

When membranes need an ESCRT: endosomal sorting and membrane remodelling in health and disease

Originally discovered as regulators of cargo sorting during endosomal trafficking, ESCRT (endosomal sorting complexes required for transport) proteins are emerging as flexible machines that shape the behaviour of membranes throughout the cell. Deregulation of ESCRT activity is observed in neuro-degenerative diseases, virus infection and cancer. However, the mechanisms of pathogenesis involving ESCRTs have not yet fully come into focus. Here, we review the current knowledge of ESCRT function in health and disease and provide educated guesses for future research and focused therapeutic intervention.

The use and application of ultrasonic vibrations in the 3D deformation of paper and cardboard

In this paper the deep drawing of cups from fiber-based materials, which is explored for some time now, is further developed through the use of micron-small vibrations in an ultrasonic frequency range within the deep-drawing tools. The design of such tools required preliminary investigations concerning the limitations of use and feasibility of this technology. These include tests for necessary clearances between punch and die, occurring pressure in this clearance, necessary punch forces and the heating of the material under the vibrational influence. According to these experiences a flexible test machine was developed enabling the examination of the deep drawing process with vibrating tools as well as its possibilities and limits. The dependence of punch force and cup quality from the ultrasonic parameters was determined and it was found that the required punch force can be reduced by up to 80% and a significant smoothing of the cup surface as well as an improved stiffness of the 3D-shapes is achieved.

Improved machinability of SiC/SiC ceramic matrix composite via laser-assisted micromachining

This study is focused on numerical modeling and experimental evaluation of laser-assisted micromachining (LAMM) of SiC/SiC ceramic matrix composite (CMC) materials. A novel experimental setup consisting of a fiber laser and the necessary optics, a three-axis CNC linear stage, and a high-speed spindle was used to implement the LAMM process. The laser-assisted micro-milling system provides unique micro-milling capabilities for flexible machining of very difficult-to-machine materials, such as ceramics, composites, and high-temperature alloys. The integrated high-power laser beam is flexibly focused on arbitrary positions around the cutting tool at a low incidence angle with a very small focused spot, thus making the system suitable for a wide range of micro-milling methods. Micro-end mills of cubic boron nitride (CBN) tools were used to perform slotting operations with and without laser preheating on CMC materials for comparative assessment. A three-dimensional (3D) transient finite-element-based thermal model was used to analytically predict appropriate process parameters on the basis of material removal temperature (Tmr). The effects of LAMM on the tool wear and tool life were evaluated experimentally. In addition, an economic analysis was carried out to compare LAMM of CMC materials with conventional micromachining methods.

A vibration damping optimization algorithm for solving a new multi-objective dynamic cell formation problem with workers training

This paper presents a comprehensive multi-objective mixed integer mathematical programming model which considers cell formation and production planning problems simultaneously. This comprehensive model includes dynamic system reconfiguration, multi period production planning, operation sequence, alternative process plans for part types, machine and worker flexibility, duplicate machines, machine capacity, available time of workers and worker assignment. The aim of the proposed model is to minimize inter and intra-cell movement costs, machine and reconfiguration costs, setup costs, production planning costs (holding, backorder and subcontracting costs) and workers hiring, firing, training and salary costs, as well as minimizing summation of machines idle times as a second objective. Due to NP-hardness of the problem, a recent and efficient meta-heuristic algorithm namely multi-objective vibration damping optimization (MOVDO) is designed for finding Pareto-optimal frontier. In order to check the efficiency of the developed algorithm, it is compared with two salient multi-objective genetic algorithms named NSGAII and NRGA. Finally, by generating some test problems in small and large scales and using some multi-objective comparison metrics, the algorithms are compared and analyzed statistically.

Multi-objective optimization of the order scheduling problem in mail-order pharmacy automation systems

This paper presents the multi-objective optimization problem (MOP) of minimizing collation delays and the makespan in mail-order pharmacy automation (MOPA) systems. MOPA is a high-throughput make-to-order (MTO) manufacturing system designed to handle thousands of prescription orders every day. Prescription orders are highly customized, and most of them consist of multiple medications that need to be collated before packaging and shipping. The completion time difference between the first and the last medications within the same order is defined as the order collation delay. This research mainly investigates the effects of machine flexibility and the proportion of multi-medication orders on the total collation delays. To solve this NP-hard problem, a genetic algorithm with a min-max Pareto objective function is used. The GA performance is compared to two industry heuristics: the longest processing time (LPT) and the least total workload (LTW). Experimental results indicate that a fully dedicated machine environment has 80 % more total collation delays as compared to a fully flexible machine environment and 25 % more total collation delays as compared to a multi-purpose machine environment. Experimental results also indicate that the GA can achieve the optimal makespan in most cases, while minimizing the total collation delays by 96 % when compared to LPT and LTW.

Valid Probabilistic Predictions for Ginseng with Venn Machines Using Electronic Nose.

In the application of electronic noses (E-noses), probabilistic prediction is a good way to estimate how confident we are about our prediction. In this work, a homemade E-nose system embedded with 16 metal-oxide semi-conductive gas sensors was used to discriminate nine kinds of ginsengs of different species or production places. A flexible machine learning framework, Venn machine (VM) was introduced to make probabilistic predictions for each prediction. Three Venn predictors were developed based on three classical probabilistic prediction methods (Platt’s method, Softmax regression and Naive Bayes). Three Venn predictors and three classical probabilistic prediction methods were compared in aspect of classification rate and especially the validity of estimated probability. A best classification rate of 88.57% was achieved with Platt’s method in offline mode, and the classification rate of VM-SVM (Venn machine based on Support Vector Machine) was 86.35%, just 2.22% lower. The validity of Venn predictors performed better than that of corresponding classical probabilistic prediction methods. The validity of VM-SVM was superior to the other methods. The results demonstrated that Venn machine is a flexible tool to make precise and valid probabilistic prediction in the application of E-nose, and VM-SVM achieved the best performance for the probabilistic prediction of ginseng samples.

Kernel machine score test for pathway analysis in the presence of semi-competing risks.

In cancer studies, patients often experience two different types of events: a non-terminal event such as recurrence or metastasis, and a terminal event such as cancer-specific death. Identifying pathways and networks of genes associated with one or both of these events is an important step in understanding disease development and targeting new biological processes for potential intervention. These correlated outcomes are commonly dealt with by modeling progression-free survival, where the event time is the minimum between the times of recurrence and death. However, identifying pathways only associated with progression-free survival may miss out on pathways that affect time to recurrence but not death, or vice versa. We propose a combined testing procedure for a pathway's association with both the cause-specific hazard of recurrence and the marginal hazard of death. The dependency between the two outcomes is accounted for through perturbation resampling to approximate the test's null distribution, without any further assumption on the nature of the dependency. Even complex non-linear relationships between pathways and disease progression or death can be uncovered thanks to a flexible kernel machine framework. The superior statistical power of our approach is demonstrated in numerical studies and in a gene expression study of breast cancer.

Considering real options in short-term decision making

Option-like situations in non-financial markets, often referred to as real options, are usually discussed and analyzed in the context of investment decisions. In spite of the real options literature’s focus on investment decisions, option-like situations are also frequently encountered in operating decisions. For instance, decisions on the operating mode of a flexible machine in the presence of switching costs can be characterized as complex real options problems with multiple compound options. For an optimal long-term solution, short-term decision rules must consider the value of these options. In this paper we first show how a fully rational decision rule that takes the long-term consequences of short-term decisions into account can be derived within the real options framework. We contrast the outcomes of decisions according to this benchmark rule with the outcomes of decisions according to the traditional decision rule based on current contribution margin and illustrate our findings with a simulation analysis providing for a rich set of environments characterized by different levels of uncertainty and different switching costs. A major drawback of the options-based rule is the necessity to estimate option values at every decision point drawing on information from all future periods. We therefore analyze how a simplified options-based decision rule that looks ahead only one period performs against the benchmark rule. In an extension of the simulation analysis we find that the simplified decision rule serves as a good heuristic and improves decision-making similar to the benchmark rule while at the same time being much more likely to be implemented in practice.

Optimization of line configuration and balancing for flexible machining lines

Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.

A New Adaptive Fuzzy PID Control Method and Its Applicance in FCBTM

<p class="Abstract">The process of tension control for material testing using the Flexible ircuit Board testing machine (FCBTM) is featured with multi-variable, nonlinearity, ime delays and time variation. In order to ensure the tension precision, the stability of ervo motor’ speed and the reliability of test results, this paper establishes an accurate ystem model for the FCBTM, in which a novel three-dimensional adaptive fuzzy ID controller is designed. Specially, the simulation results show that the proposed daptive fuzzy control method is not only robust to the external disturbance but also ith more excellent dynamic and steady-state characteristics than traditional ones.</p>

Innovative Testing Machines and Methodologies for the Mechanical Characterization of Materials

This paper is focused on the development of innovative testing machines and methodologies for the characterization of materials in working conditions similar to those found in mechanical processing of materials. Special emphasis is given to the design, fabrication, and instrumentation of a flexible drop weight testing machine, an electromagnetic compressive Hopkinson bar, and an electromagnetic cam-driven compression testing machine that are capable of performing the mechanical characterization of materials under mediumand high rates of loading. The fundamentals of plastic flow in selected forming and cutting processes are utilized to assess the validity and reliability of the proposed testing machines and associated experimental methodologies. Experimental data with technical pure Lead allows understanding the combined influence of strain, strain rate, and strain rate versus strain loading paths in the overall stress response of the materials. Results also show that the new proposed electromagnetic cam-driven compression testing machine equipped with a root type or logistic cam profile can successfully replicate the operating conditions of the two other testing machines.

An analysis of the status of resource flexibility and lean manufacturing in a textile machinery manufacturing company

Purpose – As the manufacturing industry is under pressure to face the global competition, it is necessary to improve productivity and reduce costs through minimization of wastage of resources for their survival. This paper aims to present an analysis of the status of resource flexibility and lean manufacturing through conducting a case study in an Indian textile machinery manufacturing company and also demonstrate the various areas of future scope for improving lean manufacturing. Design/methodology/approach – The case study has been conducted using the flexible system methodology (FSM) framework (Sushil, 1994). For measuring resource (labour and machine) flexibility and lean manufacturing, various factors contributing towards labour flexibility, machine flexibility and lean manufacturing are identified. To determine their relative weights, an analytical hierarchy process (AHP) has been used. A specially designed questionnaire is used to collect the information during case study on different aspects of resource flexibility and lean manufacturing. SAP-LAP analysis has also been carried out to look in to the ways the company is building up resource flexibility and lean manufacturing. Findings – The status of labour flexibility, machine flexibility and lean manufacturing is merely 49.30, 47.10 and 47.40 per cent, respectively. The most important factors of labour flexibility and machine flexibility attained a value of 59.50 and 61.17 per cent, respectively. Similarly, only 39.09 per cent wastes are eliminated through lean manufacturing. There is a huge scope to achieve a higher degree of lean manufacturing through focusing on continuous improvement, just in time (JIT) and resource flexibility factors. Research limitations/implications – The present study includes only labour and machines to compute the resource flexibility. Other resources may also be included to compute the overall resource flexibility. Practical implications – The present study provides guidelines to analyze the status of resource flexibility and lean manufacturing. According to conclusions, frail areas in the manufacturing system can be identified and a suitable course of action could be planned for the improvement. Hopefully, this study will help the firm’s management to identify the problems to manage resource flexibility and implement an effective lean manufacturing. Originality/value – In this work, the theoretical perspective has been used not only to update the original instrument, but also to study the subject from a perspective beyond that usually associated with resource flexibility and lean manufacturing.

An Enhanced Intelligent Water Drops Algorithm for Scheduling of an Agile Manufacturing System

This paper deals with an agile manufacturing system with two stages where the first stage is the machining stage including a single flexible machine while the second stage is assembly stage including parallel identical assembly machines. Products have an assembly structure where their parts should be processed at the first stage and then proceed to the assembly stage. The goal is to find the parts sequence which minimizes makespan. Since the studied problem is NP-hard, enhanced intelligent water drops (EIWD) algorithm as a new swarm-based nature inspired optimization algorithm is proposed. Also, artificial immune system (AIS) algorithm has been proposed to tackle the addressed problem. Computational results based on randomly generated instances show the effectiveness of the proposed technique.

Application of modified multi-objective particle swarm optimisation algorithm for flexible process planning problem

Process planning belongs to one of the most essential functions of the modern manufacturing system. Moreover, flexible process planning implies the ability of a system to adapt to changing requirements and thereby provide alternative ways of performing manufacturing operations on a part. Variety of manufacturing resources including variety of alternative machines, alternative tools, as well as tool access direction (TAD) leads to the fact that most of the parts in modern manufacturing systems have various flexible process plans. Therefore, obtaining optimal process plan from all available alternatives has become a very important task in the domain of flexible process planning research. In this article, a method based on modified particle swarm optimisation (mPSO) has been developed to solve this nondeterministic polynomial-hard combinatorial optimisation problem, and the following issues have been addressed: (i) the AND/OR network representation has been adopted to describe various types of flexibility, i.e. machine flexibility, tool flexibility, TAD flexibility, process flexibility and sequence flexibility; (ii) the particle encoding/decoding scheme has been proposed and traditional PSO algorithm has been modified with crossover, mutation and shift operator and (iii) optimal operation sequence has been found by performing multi-objective optimisation procedure concerning minimisation of the production time and production cost. In order to verify the performance of the proposed mPSO algorithm, five independent experiments have been carried out and comparisons with other meta-heuristic algorithms have been made. The experimental results show that the proposed algorithm has achieved satisfactory improvement in terms of efficiency and effectiveness.

Impact of Flexibility of Manufacturing System Components on Competitiveness of SMEs in Northern India

The present manufacturing environment is characterized by a number of changes which poses challenges to a typical manufacturing unit. Time demands a shift from the traditional manufacturing strategies as they do not fit to present market competition. A flexible systems strategy has to be designed for remaining competitive in the market and perform well. For designing strategies and policies it is important to know the factors that influence performance of the system. The aim of this paper is to assess the impact of the flexibility of manufacturing system components on competitiveness of SMEs in northern India. A questionnaire based survey was conducted in the SMEs across northern India analysing three sectors namely automotive, machine tool and light engineering (mechanical components and equipment). The study contributes to the existing literature by empirically investigating the impact of machine, material handling and worker flexibility on competitiveness of manufacturing firms. This paper presents a Structural Equation Model displaying the impact of flexibility of manufacturing system components on competitiveness of SMEs.