Reliability Of Manufacturing Systems Research Articles

Reliability Assessment in the Context of Industry 4.0: Data as a Game Changer

Reliability is the measure of the likelihood that a product, system or service will perform its intended function adequately for a specified period of time. Low reliability of a manufacturing system, besides the costly repairs and replacements, also implies reduced production, and consequently, significantly reduced profits. Therefore, it is very important to have a way to assess reliability, as a key performance metric for manufacturing systems, and cyber-physical systems in general. The newly developed information and communication technologies that are increasingly becoming part of the current and future manufacturing systems, both allow and invite for more sophisticated approaches to assessing reliability of manufacturing systems as opposed to the traditional expert knowledge-based approaches. In this paper, we describe the significance of evaluating reliability for the progress and acceptance of the Industry 4.0 technologies, as well as the new directions and possibilities for enhanced reliability analysis that these new technologies can provide. Finally, we provide an overview of the implications of these novel ways of analyzing reliability in the context of Industry 4.0.

Business Process Modeling in the Digital Age

Newly emerged in the Russian society trend towards digitalization is gaining increasing number of applications. Business processes modeling based on modern IT approaches has a large potential for improving the efficiency and reliability of various manufacturing systems. Unfortunately, studies that offer specific tools for formal description of manufacturing processes are rare. In this paper we propose a four-stage system for modeling business processes: design, visualization, construction of a logical model and, finally, generation of a computer code (proprietary approach to the CASE method). This technology for business processes modeling, as well as specific products based on it, can be widely used in manufacturing processes, from document workflow automation to the operation of numerically controlled machines. The proposed tool can help to increase the productivity of personnel of organizations and optimize manufacturing processes. The automatic code generation eliminates one of the main drawbacks of software development — the code does not contain input errors.

Improving operational reliability of manufacturing systems by process optimization via survival signatures

Considering that a mechanical part or component can be produced by varying process plans for specific manufacturing requirements, process optimization can be performed for some objectives, such as production quality, cost, and system reliability. The survival signature, as a reliability equivalence factor, is recently introduced to evaluate the performance reliability of a system. In this article, a survival signature–based process optimization approach is proposed to improve the operational reliability of the manufacturing process. First, a three-dimensional part model is analyzed for the identification of machining features, and the corresponding process strategies are made for creating them. Based on the feature process strategies and the current manufacturing resources, multi-process plans could be generated and a network is constructed, which illustrates the varying operation paths. Then the reliability distribution functions of the machines on the network are estimated by the failure data. Finally, the survival signatures of the network are computed and applied to measure the failure probabilities of all operation paths so that the optimal one could be selected. The feasibility and efficiency of the proposed approach have been demonstrated by a case study.

Mission reliability evaluation based on operational quality data for multistate manufacturing systems

Modern and intelligent manufacturing systems have a prominent multistate feature. However, previous studies of reliability analysis of multistate manufacturing systems mostly focused on the basic reliability of manufacturing systems but disregarded their operating characteristics, which has hindered the development of Prognostics and Health Management technique for intelligent manufacturing systems. Therefore, an evaluation approach of mission reliability for multistate manufacturing systems based on operational quality data is proposed in this paper. First, from the systematic viewpoint of the composition and operational principle of the manufacturing system, the relationship among production task execution state, production equipment degradation state, and produced product quality state is expounded, and the connotation of the mission reliability of multistate manufacturing systems is defined. Second, an extended state task network (ESTN) is presented to organise operational quality data by considering the quality state of work in process (WIP). Third, a fusion model of operational quality data for manufacturing systems is established with the aid of the ESTN, and an operational quality data-oriented evaluation method of mission reliability is been put forward. Finally, a case study of a manufacturing system for a cylinder head is conducted to verify the proposed approach.

Modelling and Computation of Equipment Reliability for Manufacturing System Based on Petri Net

For the structural complexity of the manufacturing system, it is difficult to decompose and express the equipment reliability; a three-dimensional method based on Petri nets was proposed to model and calculate equipment reliability of manufacturing systems. This method includes three steps: The first step is to model the equipment chain network according to manufacturing process by Petri nets, and the reduction method of series and parallel Petri nets is used to simplify the complexity of Petri nets; The second step is to model each single equipment reliability by tree Petri nets, fault tree analysis (FTA) is adopted to express single equipment reliability, and then FTA is converted to tree Petri nets according to the conversion rule between them; The third step is to integrate chain and tree Petri nets into three-dimensional Petri nets to express the whole equipment reliability of manufacturing system. Finally, the reliability calculation of engine cylinder manufacturing system is taken as an example to verify the proposed method.

Joint production, quality and maintenance control of a two-machine line subject to operation-dependent and quality-dependent failures

In the literature of operations management, the reliability of multistage manufacturing systems has been always modeled with uncorrelated failure processes where the reliability of each machine is assumed to be independent of any failure in the other machines. However, in real-life, machines may be subject to complex correlated failures such as increased degradation and tool wear caused by defective parts produced in preceding machines. Ignoring the correlation effect when modeling the reliability of multistage systems generally results in inaccurate estimation of the overall system reliability and inefficient operations policy accordingly. In this paper, we deal with the problem of integrated production, quality and maintenance control of production lines where machines are subject to quality and reliability operation-dependent degradation. Also, machines' reliability is correlated with the level of incoming product quality. For illustration, we study in this paper a two-machine line model. We propose a combined mathematics and simulation-based modeling framework to jointly optimize the production, quality and maintenance control settings. The objective is to minimize the total cost incurred under a constraint on the outgoing quality. Numerical examples are given to show the effectiveness of the resolution approach and to study important aspects in multistage systems such as the allocation of inspection and maintenance efforts, the Quality-Reliability chain and the interdependence between production, quality and maintenance control settings. The results obtained demonstrate that failure correlation has a significant impact on the optimal control settings and that maintenance and quality control activities in preceding stages can play an important role in the reliability improvement of the subsequent machines.

Quality by design approaches for pharmaceutical development and manufacturing of Chinese medicine

The pharmaceutical quality was built by design, formed in the manufacturing process and improved during the product's lifecycle. Based on the comprehensive literature review of pharmaceutical quality by design (QbD), the essential ideas and implementation strategies of pharmaceutical QbD were interpreted. Considering the complex nature of Chinese medicine, the "4H" model was innovated and proposed for implementing QbD in pharmaceutical development and industrial manufacture of Chinese medicine product. "4H" corresponds to the acronym of holistic design, holistic information analysis, holistic quality control, and holistic process optimization, which is consistent with the holistic concept of Chinese medicine theory. The holistic design aims at constructing both the quality problem space from the patient requirement and the quality solution space from multidisciplinary knowledge. Holistic information analysis emphasizes understanding the quality pattern of Chinese medicine by integrating and mining multisource data and information at a relatively high level. The batch-to-batch quality consistence and manufacturing system reliability can be realized by comprehensive application of inspective quality control, statistical quality control, predictive quality control and intelligent quality control strategies. Holistic process optimization is to improve the product quality and process capability during the product lifecycle management. The implementation of QbD is useful to eliminate the ecosystem contradictions lying in the pharmaceutical development and manufacturing process of Chinese medicine product, and helps guarantee the cost effectiveness.

A simulation analysis of the impact of finite buffer storage on manufacturing system reliability

This paper develops a Monte Carlo Simulation (MCS) approach to estimate the system reliability for a multistate manufacturing network with parallel production lines (MMN-PPL) considering finite buffer storage. System reliability indicates the probability that all workstations provide sufficient capacity to satisfy a specified demand and buffers possess adequate storage. The buffers are modeled as a network-structured MMN-PPL. Storage usage of buffers is analyzed based on the MMN-PPL. MCS algorithms are developed to generate the capacity state and to check the storage usage of buffers to determine whether the demand can be satisfied or not. System reliability of the MMN-PPL is estimated through simulation. The MCS approach is an efficient method to estimate system reliability for an MMN-PPL with a reasonable accuracy and time. A pair of practical examples including a tile and a touch panel manufacturing systems shows that system reliability is overestimated when buffer storage is assumed to be infinite. Demand satisfaction probability is further addressed to provide guidance for a proper production policy.

Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach

The business performance of manufacturing organizations depends on the reliability and productivity of equipment, machineries and entire manufacturing system. Therefore, the main role of maintenance and production managers is to keep manufacturing system always up by adopting most appropriate maintenance methods. There are alternative maintenance techniques for each machine, the selection of which depend on multiple factors. The contemporary approaches to maintenance technique selection emphasize on operational needs and economic factors only. As the reliability of production systems is the strategic intent of manufacturing organizations, maintenance technique selection must consider strategic factors of the concerned organization along with operational and economic criteria. The main aim of this research is to develop a method for selecting the most appropriate maintenance technique for manufacturing industry with the consideration of strategic, planning and operational criteria through involvement of relevant stakeholders. The proposed method combines quality function deployment (QFD), the analytic hierarchy process (AHP) and the benefit of doubt (BoD) approach. QFD links strategic intents of the organizations with the planning and operational needs, the AHP helps in prioritizing the criteria for selection and ranking the alternative maintenance techniques, and the BoD approach facilitates analysing robustness of the method through sensitivity analysis through setting the realistic limits for decision making. The proposed method has been applied to maintenance technique selection problems of three productive systems of a gear manufacturing organization in India to demonstrate its effectiveness.

Reliability-oriented quality control approach for production process based on RQR chain

Reliability assurance is a series of activities that ensure that the product reliability requirements be realised in a product life cycle. However, as reliability assurance activities are usually only implemented in design and usage, the integration of reliability assurance with quality control in production has not attracted the attention it deserved, thereby hindering production performance improvement to satisfy increasingly stringent customer requirements. To this end, this paper proposes a reliability-oriented quality control framework to integrate quality control and reliability assurance in production according to the principles of total quality management (TQM). Firstly, from the integrated quality and reliability assurance perspective, the RQR chain is proposed to represent the bidirectional relationships among the three basic management objects in a production process, namely, manufacturing system reliability (R), manufacturing process quality (Q), and the produced product reliability (R). Secondly, a reliability-oriented quality control framework for the production process based on the RQR chain is presented to provide the control clue for a manufacturing enterprise. Thirdly, the validity of the proposed approach is verified in a vehicle engine manufacturing enterprise of China. The proposed RQR chain as a decision-support model for TQM is eventually proven effective in promoting the integration of quality control and reliability assurance in production.

Dynamic decision-making for reliability and maintenance analysis of manufacturing systems based on failure effects

ABSTRACTA framework for reliability and maintenance analysis of job shop manufacturing systems is proposed in this paper. An efficient preventive maintenance (PM) policy in terms of failure effects analysis (FEA) is proposed. Subsequently, reliability evaluation and component importance measure based on FEA are performed under the PM policy. A job shop manufacturing system is applied to validate the reliability evaluation and dynamic maintenance policy. Obtained results are compared with existed methods and the effectiveness is validated. Some vague understandings for issues such as network modelling, vulnerabilities identification, the evaluation criteria of repairable systems, as well as PM policy during manufacturing system reliability analysis are elaborated. This framework can help for reliability optimisation and rational maintenance resources allocation of job shop manufacturing systems.

Multisensory fusion based virtual tool wear sensing for ubiquitous manufacturing

Pervasiveness of ubiquitous computing advances the manufacturing scheme into a ubiquitous manufacturing era which poses significant challenges on sensing technology and system reliability. To improve manufacturing system reliability, this paper presents a new virtual tool wear sensing technique based on multisensory data fusion and artificial intelligence model for tool condition monitoring. It infers the difficult-to-measure tool wear parameters (e.g. tool wear width) by fusing in-process multisensory data (e.g. force, vibration, etc.) with dimension reduction technique and support vector regression model. Different state-of-the-art dimension reduction techniques including kernel principal component analysis, locally linear embedding, isometric feature mapping, and minimum redundancy maximum relevant method have been investigated for feature fusion in a virtual sensing model, and the kernel principal component analysis performs best in terms of sensing accuracy. The effectiveness of the developed virtual tool wear sensing technique is experimentally validated in a set of machining tool run-to-failure tests on a computer numerical control milling machine. The results show that the estimated tool wear width through virtual sensing is comparable to that measured offline by a microscope instrument in terms of accuracy, moreover, in a more cost-effective manner. A multi-sensory fusion based virtual tool wear sensing model is developed.KPCA performs best among the dimension reduction techniques investigated.The virtual tool wear sensing model is validated using a machining tool life test.The performance of the model is comparable to the costly offline instrumentation.

Reliability Modeling and Optimization Strategy for Manufacturing System Based on RQR Chain

Accurate and dynamic reliability modeling for the running manufacturing system is the prerequisite to implement preventive maintenance. However, existing studies could not output the reliability value in real time because their abandonment of the quality inspection data originated in the operation process of manufacturing system. Therefore, this paper presents an approach to model the manufacturing system reliability dynamically based on their operation data of process quality and output data of product reliability. Firstly, on the basis of importance explanation of the quality variations in manufacturing process as the linkage for the manufacturing system reliability and product inherent reliability, the RQR chain which could represent the relationships between them is put forward, and the product qualified probability is proposed to quantify the impacts of quality variation in manufacturing process on the reliability of manufacturing system further. Secondly, the impact of qualified probability on the product inherent reliability is expounded, and the modeling approach of manufacturing system reliability based on the qualified probability is presented. Thirdly, the preventive maintenance optimization strategy for manufacturing system driven by the loss of manufacturing quality variation is proposed. Finally, the validity of the proposed approach is verified by the reliability analysis and optimization example of engine cover manufacturing system.

A fuzzy control system to adjust the number of cards in a CONWIP-based manufacturing system

The research presented in this paper concerns a dynamic control card strategy to capture the market changes and keep a high level of the performance measures. The methodology proposed is based on the development of a fuzzy controller that adjusts the number of cards. The inputs of the fuzzy controller are the observation of the demand fluctuations and the throughput rate of the manufacturing system. The throughput rate detects the state of the manufacturing system while the demand fluctuations try to forecast the demand fluctuations. The demand fluctuations are evaluated computing two averages: the first on a medium horizon and the second on a short horizon. A discrete event simulation environment based on Rockwell ARENA® platform is developed to test the proposed approach. The benefits of the fuzzy approach are more relevant in case of demand and uncertainty processing times considering the reliability of the manufacturing system.

Research on the Tool Management System Based on Web

The tool management is an important part in FMS (the flexible manufacturing system), especially for single or small batch processing operation plan. The scientific rationality of the tool management determines the manufacturing system reliability and production efficiency. To establish a set of tool management system based on Web, make the tool entity information of manufacturing execution system to be digitized, and realize the information sharing in the different processing unit or between enterprise alliances through the Internet, will greatly improve the production efficiency and reduce the production cost.

System reliability evaluation of a touch panel manufacturing system with defect rate and reworking

In recent years, portable consumer electronic products, such as cell phone, GPS, digital camera, tablet PC, and notebook are using touch panel as interface. With the demand of touch panel increases, performance assessment is essential for touch panel production. This paper develops a method to evaluate system reliability of a touch panel manufacturing system (TPMS) with defect rate of each workstation and takes reworking actions into account. The system reliability which evaluates the possibility of demand satisfaction can provide to managers with an understanding of the system capability and can indicate possible improvements. First, we construct a capacitated manufacturing network (CMN) for a TPMS. Second, a decomposition technique is developed to determine the input flow of each workstation based on the CMN. Finally, we generate the minimal capacity vectors that should be provided to satisfy the demand. The system reliability is subsequently evaluated in terms of the minimal capacity vectors. A further decision making issue is discussed to decide a reliable production strategy.

Research on Dynamic Programming of the Series Manufacturing System Reliability Allocation

Research on Dynamic Programming of the Series Manufacturing System Reliability Allocation

Scheduling of energy flows for parallel batch processes using max-plus systems

A common approach to increase reliability and efficiency of manufacturing systems is optimal scheduling. In this paper, we consider scheduling problems for a specific type of systems where batch processes are running in parallel. The goal is to schedule the interaction between the parallel processes, in the form of energy flows, to minimize a desired objective. We make use of a max-plus approach in the formulation of the scheduling problem and use this formulation in the optimization subsequently. This framework has been used to formulate and optimize a case study for the production of calcium silicate stones.

Morphological Filtering Algorithm for Estimation of Tool Wear in CNC Milling Machining

Estimation of tool condition has very important meaning to improve the product quality, continuous machining ability and reliability of the manufacturing system. Based on mathematical morphology, a systematic approach is developed to implement online estimation of tool wear in this paper. As the nonlinear filter, morphological filter is selected to reduce the higher frequency noises before feature values extraction. The feature vector consists of original characteristics of vibration signal and cutting force signal. Then, they are input into SVM for training and testing. Experiments show that this method can achieve tool wear estimation effectively.

A Cost Analysis of Systems Subject to Random Field Environments and Reliability

We present a generalized cost model subject to random field environments with considerations of cost to remove failures during testing and warranty periods, and penalty cost due to the system failures. We also determine the optimal release time policies that minimize the expected system cost. Many scientific contributions have been developed in software reliability modeling, while none has studied the manufacturing or industrial system reliability growth yet, considering also the differences between testing and operating environments. The application of the proposed model, in comparison to the nonhomogenous Poisson process Goel-Okumoto model, to an industrial application is discussed to illustrate how the proposed model can be used in practice.