Critical Machine Research Articles

A Novel Quantum Immune Algorithm for Multiobjective Flexible Job Shop Scheduling

In this study, a hybrid of Quantum Evolutionary and Artificial Immune Algorithms (QIA) is proposed for solving Multiobjective Flexible Job Shop Scheduling Problem (MFJSSP). This problem is formulated as three-objective problem which minimizes completion time (makespan), critical machine workload and total work load of all machines. The quantum coding is shown to improve the immune strategy. The proposed algorithm overcomes the problem by increasing the speed of convergence and diversity of population. Three benchmarks of Kacem and Brandimart are examined to evaluate the performance of the proposed algorithm. The experimental results show a better performance in comparison to other approaches.

Transient Stability Emergency Control Research Based on Critical Machine Unit

Self-healing ability is the basic requirement of smart grid. When a fault occurs, the control system should analysis transient stability on line and offer control measures quickly. This paper presents a fast and accurate transient stability emergency control measure. Based on the wide-area measures system, the sensitivity of critical-machine-unit stability index to controlled parameter is derived, and as one of transient stability constraints, sensitivity equation is incorporated into the nonlinear optimization algorithm to obtain the required emergency control amount. The method is simple and quick; the smallest cutting amount ensures load power supply, the simulation verifies the method’s superiority.

Minimizing Material Processing Time and Idle Time of a Critical Machine in a Flow Shop

In this research article aims to develop a heuristic for minimizing the total material processing time and idle time of the critical machine in a flow shop. This heuristic is proposed through the Exponential Distribution (ED) factor which helps in developing a mathematical model with less computational instance. When the idle time of the critical machine is reduced then it is indirectly affects the total material processing time of the flow shop, which makes the objective of critical machine utilization as vital. And a set of constrain had been established to position the critical machines in the flow shop. For several instance, computational experiments had done using the benchmark problems, among other heuristics ED heuristic yields a better result.

Reading Machines: On the Surface of Meaning – Beyond the Surface of Discourse

Reading machines are technological devices promising to support or even perfect processes of reading. Although the concept of reading machines is almost as old as the notion of writing machines, it has received far less attention in literary and cultural studies. The following essay addresses this gap. The first part of the argument links the reading machine to Freud’s definition of a tool. As a prosthesis connected to the human body and mind, a tool produces ‘trouble at times’: translation difficulties between the machine and its user affecting matters of materiality, discourse, and meaning alike. The reading machine embodies such ‘trouble at times’ that results from the paradox tension between machine and meaning. While the machine requires the mechanized processes to be unambiguous, the reading process is ambiguous by definition. Most of the reading machines invented in the past decades, do not take into account the trouble that results from such a tension: first and foremost, they serve to support reading processes mechanically. Yet, some of them stand out and hold a specific potential to stage such troubles and render the underlying tensions productive. The article discusses three of them, each of them focussing on a different aspect of the reading process: the first one is a ‘pedagogical reading machine’ (1767) concerned with the alphabetization process, the second one is an ‘aesthetic reading machine’ (1930) designed for reading literary texts, and the third one is a ‘critical reading machine’ (2007) that focuses on literary criticism.

A Hybrid Discrete Firefly Algorithm for Multi-Objective Flexible Job Shop Scheduling Problems with Maintenance Activity

This paper presents a novel hybrid discrete firefly algorithm (HDFA) for solving the multi-objective flexible job shop scheduling problem with non fixed availability constraints (FJSP-nfa) due to maintenance activity. Three minimization objectives-the maximum completion time, the workload of the critical machine and the total workload of all machines are considered simultaneously. In this study, the discrete firefly algorithm is adopted to solve the problem, in which the machine assignment and operation sequence are processed by constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. In addition the decoding mechanism considering the maintenance activity is presented. A neighbourhood based local search is hybridized to enhance the exploitation capability. Representative benchmark problems are solved in order to evaluate and study the performance of the proposed algorithm.

A hybrid discrete firefly algorithm for multi-objective flexible job shop scheduling problem with limited resource constraints

In this paper, a hybrid discrete firefly algorithm is presented to solve the multi-objective flexible job shop scheduling problem with limited resource constraints. The main constraint of this scheduling problem is that each operation of a job must follow a process sequence and each operation must be processed on an assigned machine. These constraints are used to balance between the resource limitation and machine flexibility. Three minimisation objectives—the maximum completion time, the workload of the critical machine and the total workload of all machines—are considered simultaneously. In this study, discrete firefly algorithm is adopted to solve the problem, in which the machine assignment and operation sequence are processed by constructing a suitable conversion of the continuous functions as attractiveness, distance and movement, into new discrete functions. Meanwhile, local search method with neighbourhood structures is hybridised to enhance the exploitation capability. Benchmark problems are used to evaluate and study the performance of the proposed algorithm. The computational result shows that the proposed algorithm produced better results than other authors’ algorithms.

Profile monitoring via sensor fusion: the use of PCA methods for multi-channel data

Continuous advances of sensor technology and real-time computational capability are leading to data-rich environments to improve industrial automation and machine intelligence. When multiple signals are acquired from different sources (i.e. multi-channel signal data), two main issues must be faced: (i) the reduction of data dimensionality to make the overall signal analysis system efficient and actually applicable in industrial environments, and (ii) the fusion of all the sensor outputs to achieve a better comprehension of the process. In this frame, multi-way principal component analysis (PCA) represents a multivariate technique to perform both the tasks. The paper investigates two main multi-way extensions of the traditional PCA to deal with multi-channel signals, one based on unfolding the original data-set, and one based on multi-linear analysis of data in their tensorial form. The approaches proposed for data modelling are combined with appropriate control charting to achieve multi-channel profile data monitoring. The developed methodologies are demonstrated with both simulated and real data. The real data come from an industrial sensor fusion application in waterjet cutting, where different signals are monitored to detect faults affecting the most critical machine components.

Maintainability analysis in the yogurt industry

Maintainability is used to improve the performance of the system based on the adequate maintenance activities. In this paper, the maintainability characteristics and the critical machines of the yogurt production line with respect to repair frequency and duration were identified. Descriptive statistics of the repair data were carried out and the best fitness index parameters were determined. Data collection from the production line and their analysis were valid for a period of thirty months. Furthermore, the maintainability and repair rate modes for the entire production line were calculated. Moreover, maintainability for different time periods for all the machines and the line have been estimated on the basis of fitted distribution models. This study is anticipated to serve as a valid data source for yogurt product machinery manufacturers, who wish to improve the design and operation of their production lines.

Induction Hardening of Carbon Steel Material: The Effect of Specimen Diameter

Induction hardening is well developed technology in many industrial applications, e.g. automotive, tool manufacturing, casting technology, sheet metal forming etc. The surface hardened medium carbon steels are widely used for critical automotive and machine components such as propulsion shafts, crankshafts and steering knuckles which require high fatigue resistance. However, some of small and medium sized enterprises, focused in metal manufacturing in Indonesia have not complete practical knowledge in employing induction hardening to harden the mechanical components. This paper present a technical report of induction hardening process for medium carbon steel material with considering the effect of specimen diameter. The results show that the increase of the specimen diameter increases the current input requirement which also increase the power requirement as a consequence. The induction frequency is automatically decrease when the specimen diameter is increase and resulted in the deeper hardening layer on the surface. The hardness layer of specimen A ranges from outer surface to 6 mm from the surface whereas specimen B ranges from outer surface to 10 mm from the surface from. The micro structure evolution from the surface to the center of the specimen for the both specimen is almost similar. It is mostly affected by the heating temperature and heat distribution from the surface to the center of specimen.

A Survey on Occurrence of Critical Machines in a Manufacturing Environment

The modern manufacturing environment is generally expressed in terms of flowshop, where all the machines are considered equally, despite the availability of critical machines. Here, a survey was made on the manufacturing environment to identify the critical machines in it. The critical machine is identified based on processing time, operation, maintenance requirement, automation, life, breakdown, buffer or delay time, rental cost, and so on. Mostly, the scheduling was done to reduce the makespan and total completion time. These objectives are indirectly achieved by effective utilization of critical machine. The need to develop heuristics becomes vital to achieve these objectives. Though many heuristics are successful, it does not concentrate on critical machine but the role of critical machines in a flowshop becomes essential. This Study was done to analyze the maximum possibilities and effective utilization of critical machines in a flowshop. Many researchers focused on the critical machines at its first stage, but very few reports are available on its second stage and further stages. The tedious task with the critical machines can be made easier by new solution methods. This article focused on the possibility of critical machine, position of critical machine and the need of a hybrid flowshop in the modern manufacturing environment for the effective management of the critical machines.

Optimization of Makespan in Job and Machine Priority Environment

This paper analyses a specific case of permutation flow shop scheduling problem with job and machine priority. Sometimes, a particular job has to precede or succeed another job; or a set of jobs are to be together for a specific reason. Within the set of jobs also, there may be a condition that a particular job has to precede or succeed another job. In such case, the scheduling is done in two or more phases to optimize the makespan. In many occasions, the percentage utilization of a particular machine has to be increased due to several reasons. The machine may be costlier, rented, and highly precise or needs to be operated continuously. In the context of the permutation flow shop scheduling, the percentage utilization is calculated in terms of machining time compared with the makespan. For a fixed number of jobs, the total machining time for each machine is also fixed and reduction in the makespan only can increase the percentage utilization. On the other hand, splitting the machining times and regrouping may also help for achieving the objective. The problem is demonstrated with numerical examples. For trial purpose, the machining time of all the jobs that come before and after the priority machine are split (25% and 50%) individually and also in toto, and combined with the critical machine. The number of jobs and machines is kept the same. Consequently, the makespan and percentage utilization have been computed and compared with the original case.

Multi-objective flexible job shop scheduling using hybrid differential evolution algorithm

The authors addressed multi objective flexible job shop scheduling problems using hybrid differential evolution algorithm for minimisation of makespan, total machine load and critical machine load. The differential evolution algorithm is a stochastic-based adaptive scheme used for global optimisation over continuous space and to apply it for flexible job shop scheduling problem a suitable encoding mechanism is required. In this work random keys encoding mechanism is used to generate schedules that deals with floating point vectors. A non-dominated sorting algorithm is used to find the set of non-dominated solutions for the given scheduling problem. The proposed approach is extensively tested on a set of standard flexible job shop scheduling instances reported in the literature and it is found that the proposed algorithm is performing well on all the test problems.

Recovery Effect in Drawing of Steel Bar for Sizing

Dimensional accuracy characterized by limit deviation in diameter is of great importance for the sized steel used for critical machine parts and tool production. Sized steel is manufactured by cold drawing with small single reductions. One of the ways to improve the dimensional accuracy is to take into account the recovery effect. As a result of the effect above the sized steel diameter after drawing is a bit larger than the die bearing diameter in the non-loaded condition. For some predetermined combinations of the drawing process factors the recovery value is quite comparable with the diameter tolerance limit determined by standards. It is especially characteristic for sized steel more than 10mm in diameter with yield strength of more than 400MPa. The study describes the investigation results of the drawing process factors influence the value of sized steel recovery. Using the finite elements method the authors carried out simulation of stress and strain state in the deformation zone during drawing. It was proved that there was a relationship between the radial stresses developed on the sized steel surface on the exit from the die bearing zone and the recovery value. The research group determined the dependence of recovery value on the degree of reduction, the coefficient of contact friction, the die semi-angle and the die bearing length, the bar yield strength and its diameter. The obtained results make it possible to determine the parameters of sized steel drawing with the preset diameter limit deviation taking into account the recovery effect within a wide deviation range of processing factors.

A discrete artificial bee colony algorithm for the multi-objective flexible job-shop scheduling problem with maintenance activities

This paper presents a novel discrete artificial bee colony (DABC) algorithm for solving the multi-objective flexible job shop scheduling problem with maintenance activities. Performance criteria considered are the maximum completion time so called makespan, the total workload of machines and the workload of the critical machine. Unlike the original ABC algorithm, the proposed DABC algorithm presents a unique solution representation where a food source is represented by two discrete vectors and tabu search (TS) is applied to each food source to generate neighboring food sources for the employed bees, onlooker bees, and scout bees. An efficient initialization scheme is introduced to construct the initial population with a certain level of quality and diversity. A self-adaptive strategy is adopted to enable the DABC algorithm with learning ability for producing neighboring solutions in different promising regions whereas an external Pareto archive set is designed to record the non-dominated solutions found so far. Furthermore, a novel decoding method is also presented to tackle maintenance activities in schedules generated. The proposed DABC algorithm is tested on a set of the well-known benchmark instances from the existing literature. Through a detailed analysis of experimental results, the highly effective and efficient performance of the proposed DABC algorithm is shown against the best performing algorithms from the literature.

The optimal number of used machines in a two-stage flexible flowshop scheduling problem

We study practical scheduling problems with a major decision referring to the number of machines to be used. We focus on a two-stage flexible flowshop, where each job is processed on the first (critical) machine, and then continues to one of the second-stage parallel machines. Jobs are assumed to have identical processing times, and are processed in batches. A setup time is required when starting a new batch. We consider two objective functions: minimum makespan and minimum flowtime. In both cases, a closed form expression for the optimal number of machines to be used is introduced, and a unique and unusual sequence of decreasing batch sizes is shown to be optimal.

Dual Generator Cluster Transient Stability Assessment Using Swallowtail Catastrophe Theory

In this paper swallowtail catastrophe is used to determine the transient stability regions. The bifurcation set represents the transient stability region in terms of power system transient parameters bounded by the transient stability limits. The system modelling is generalized in such, that the analysis could handle either one or any number of critical machines. This generalized model is then tested on a New England 39bus 10-machine power system. The results of the stability analysis done with the generalized method are compared with the time solution and the results were satisfactory. The transient stability regions determined are valid for any changes in loading conditions and fault location. This method is a good candidate for on-line assessment of transient stability of power systems.

Maintenance Optimization for Asset Systems With Dependent Performance Degradation

This paper presents a model for optimizing maintenance plans for an industrial system consisting of a number of assets with degradation and performance interaction between them. In particular, we consider an asset system with M identical non-critical machines feeding their output to a critical machine. A common repair team performs maintenance on all the machines. All the machines deteriorate over time stochastically independently. In addition to the stochastically independent degradation, the degradation of the non-critical machines also affects the performance of the critical machine. We develop a mathematical model to represent these interactions and performance of the asset system. We also provide a simulation-based numerical solution to optimize the maintenance plan for the system outlining the maintenance intervals for each of the machines.

Implementation of Autonomous Maintenance in Semiconductor Industry: A Case Study

Maintenance is a vital component in ensuring machines to run smoothly. While, maintenance technicians are responsible in conserving the conditions of machine by performing regular inspections. This study was conducted to investigate the performance of maintenance system in a company by identifying the critical machine with the highest breakdown frequency and time. It was found that high breakdown was due to the high workload of technicians, where no extra time can be allocated for thorough inspection task. Technicians do not have enough support in performing maintenance task. In this paper, Autonomous Maintenance (AM) program is suggested to reduce technicians’ workload through operators’ involvement. Technicians work is reduced with the aid of operators, which gives them more time for other maintenance tasks. The AM process flow is implemented in a case study company as a verification and validation processes.

A two-stage flow shop scheduling with a critical machine and batch availability

AbstractWe study a two-stage flowshop, where each job is processed on the first (critical) machine, and then continues to one of two second-stage (dedicated) machines. We assume identical (but machine-dependent) job processing times. Jobs are processed on the critical machine in batches, and a setup time is required when starting a new batch. The setting assumes batch-availability, i.e., jobs become available for the second stage only when their entire batch is completed on the critical machine. We consider three objective functions: minimum makespan, minimum total load, and minimum weighted flow-time. Polynomial time dynamic programming algorithms are introduced, which are numerically shown to be able to solve problems of medium size in reasonable time. A heuristic for makespan minimization is presented and shown numerically to be both accurate and efficient.

Superhydrophilic surface on Cu substrate to enhance lubricant retention

The loss of lubricant from the surfaces of critical machine parts often leads to friction and heat-related failures which can cause catastrophic damage to machinery. In this study, the effect of micro- and nano-texturing on lubricant retention was investigated. Micro-textures were produced by sandblasting Cu substrates, while nano-textures were created by aluminum-induced crystallization of amorphous silicon. The topography and the wettability of the textured surfaces were characterized by means of scanning electron microscopy and a video-based optical contact angle measuring system, respectively. The lubricant retention on the textured surfaces was investigated using a dynamic method. It was found that superhydrophilic surfaces created by the combined micro- and nano-texturing technique can significantly enhance the lubricant retention on Cu substrates.