Monitoring System of Vibroacoustic Parameters of a Working Zone

This article discusses the safety problems of the use of aviation technology associated with the influence of operational vibration of aircraft. The topical issue of timely detection and prevention of a dangerous state of critical machines and mechanisms is analyzed. Modern means of measuring vibration parameters, principles of measurement, as well as characteristics of the sensitive element of the measuring transducer, are considered. The block diagram and operation algorithm of the proposed system for monitoring vibroacoustic parameters, which is built on the basis of a piezoelectric transducer, is presented. This system can measure the parameters of noise and vibration and analyze the measured data, signal about exceeding the permissible ranges for human work, display the measured data. The advantage of the proposed system is the connection of the measuring channels with the mainboard using the Bluetooth module, which allows the sensors to measure noise and vibration to be placed in any part of the working area.

Effect of Preventive Maintenance on Machine Reliability in a Beverage Packaging Plant

This paper investigates the effect of preventive maintenance on the reliabilities of devices in a bottling plant. Six months of real-time maintenance data were analyzed quantitatively. Based on the breakdown events obtained for each machine, mean time between failure (MTBF), mean time to repair (MTTR), and failure rate (λ) values for individual equipment are calculated. The bottle packer, empty bottle inspector (EBI), and palletizer are identified as the plant's critical machines. A breakdown analysis (BDA) is then performed on the bottle packer and from the failure mode of all the reoccurring problems affecting this machine as a result of ineffective PM. An autonomous maintenance (AM) team is set up as part of establishing an effective PM program to improve the reliabilities of the critical machines that were continually falling. A significant reduction in machine breakdowns is observed after two months of rolling out the AM program. As a result, the reliability of bottle packer increased from 55.30% to 70.80%, while EBI and palletizer increased from 89.20% and 87.20% to 92% and 90.50%, respectively.

Improving Production Performance Through Multi-Plant Cross Learning

The advancement in Web-/Internet-based technologies and applications in manufacturing sector have increased utilization of cyber workspace to enable more efficient and effective ways of doing manufacturing from distributed locations. This work introduces a novel continuous improvement framework to improve the performance of production lines through multi-plant comparison and learning among identical or similar production lines in different locations by leveraging the information stored on factory cloud. In this work, production data from multiple identical production lines are collected and analyzed to learn the “best” feasible action on critical machines, which offers a new way to optimize the management of product lines. Machine learning and system model are used to find the relationships between the performance index and the available data. A real case study based on multiple similar automotive plants is provided to demonstrate the method and the increase of throughput is predicted.

A hybrid reliability-centered maintenance approach for mining transportation machines: a real case in Esfahan

PurposeThe purpose of this study is to propose a hybrid reliability-centered maintenance (RCM) approach for mining transportation machines of a limestone complex, a real case in Esfahan, Iran.Design/methodology/approachCriteria for selecting critical machines were collected within literature and selected by decision-makers (DCs), and critical machines have been identified using the preference ranking organization method for enrichment of evaluations (PROMETHEE). Also, multi-criteria decision-making (MCDM) methods were used in addition to failure mode, effects and criticality analysis (FMECA) for selecting and prioritizing high-risk failures as well as optimizing the RCM performance. More specifically, the criteria of severity, detectability and frequency of occurrence were selected for risk assessment based on the previous studies, and were weighted using the analytic hierarchy process (AHP) method. Also, the technique for order of preference by similarity to ideal solution (TOPSIS) has been applied to prioritize failures' risk. Finally, the critical failures were inserted in the RCM decision-making worksheet and the required actions were determined for them.FindingsAccording to the obtained values from PROMEHTEE method, the machine with code 739-7 was selected as the first priority and the most critical equipment. Further, based on results of TOPSIS method, the failure mode of “Lubrication hole clogging in crankpin bearing due poor quality oil,” “Deformation of main bearing due to overwork” and “The piston ring hotness due to unusual increase in the temperature of cylinder” have the highest risks among failure modes, respectively.Originality/valueRCM has been deployed in various studies. However, in the current study, a hybrid MCDM-FMECA has been proposed to cope with high-risk failures. Besides, transportation machineries are one of the most critical equipment in the mining industry. Due to noticeable costs of this equipment, effective and continuous usage of this fleet requires the implementation of proper maintenance strategy. To the best of our knowledge, there is no research which has used RCM for transportation systems in the mining sector, and therefore, the innovation of this research is employment of the proposed hybrid approach for transportation machineries in the mining industry.

USBCaptchaIn: Preventing (un)conventional attacks from promiscuously used USB devices in industrial control systems1

Industrial Control Systems (ICS) are sensible targets for high profile attackers and advanced persistent threats, which are known to exploit USB thumb drives as an effective spreading vector. In ICSes, thumb drives are widely used to transfer files among disconnected systems and represent a serious security risks, since, they may be promiscuously used in both critical and regular systems. The threats come both from malware hidden in files stored in the thumb drives and from BadUSB attacks. BadUSB leverages the modification of firmware of USB devices in order to mimic the behaviour of a keyboard and send malicious commands to the host. We present a solution that allows a promiscuous use of USB thumbs drives while protecting critical machines from malware, that spreads by regular file infection or by firmware infection. The main component of the architecture we propose is an hardware, called USBCaptchaIn, intended to be in the middle between critical machines and connected USB devices. We do not require users to change the way they use thumb drives. To avoid human-errors, we do not require users to take any decision. The proposed approach is highly compatible with already deployed products of a ICS environment and proactively blocks malware before they reach their targets. We describe our solution, provide a thorough analysis of the security of our approach in the ICS context, and report the informal feedback of some experts regarding our first prototypes.

Degradation of Lon in Caulobacter crescentus

ABSTRACT Protein degradation is an essential process in all organisms. This process is irreversible and energetically costly; therefore, protein destruction must be tightly controlled. While environmental stresses often lead to upregulation of proteases at the transcriptional level, little is known about posttranslational control of these critical machines. In this study, we show that in Caulobacter crescentus levels of the Lon protease are controlled through proteolysis. Lon turnover requires active Lon and ClpAP proteases. We show that specific determinants dictate Lon stability with a key carboxy-terminal histidine residue driving recognition. Expression of stabilized Lon variants results in toxic levels of protease that deplete normal Lon substrates, such as the replication initiator DnaA, to lethally low levels. Taken together, results of this work demonstrate a feedback mechanism in which ClpAP and Lon collaborate to tune Lon proteolytic capacity for the cell. IMPORTANCE Proteases are essential, but unrestrained activity can also kill cells by degrading essential proteins. The quality-control protease Lon must degrade many misfolded and native substrates. We show that Lon is itself controlled through proteolysis and that bypassing this control results in toxic consequences for the cell.

Degradation of Lon in Caulobacter crescentus

Protein degradation is an essential process in all organisms. This process is irreversible and energetically costly; therefore, protein destruction must be tightly controlled. While environmental stresses often lead to upregulation of proteases at the transcriptional level, little is known about post-translational control of these critical machines. In this study we show that in Caulobacter crescentus levels of the Lon protease are controlled through proteolysis. Lon turnover requires active Lon and ClpAP proteases. We show that specific determinants dictate Lon stability with a key carboxy-terminal histidine residue driving recognition. Expression of stabilized Lon variants results in toxic levels of protease that deplete normal Lon substrates such as the replication initiator DnaA to lethally low levels. Taken together, this work demonstrates a feedback mechanism in which ClpAP and Lon collaborate to tune Lon proteolytic capacity for the cell.ImportanceProteases are essential, but unrestrained activity can also kill cells by degrading essential proteins. The quality control protease Lon must degrade many misfolded and native substrates. We show that Lon is itself controlled through proteolysis and that bypassing this control results in toxic consequences for the cell.

Analysis of critical machine reliability in manufacturing cells

Purpose: In an increasingly competitive business environment, machine reliability problem merits special attention in operations of manufacturing cells. This is mainly due to flow line nature of the cellular layout, interdependency of downstream and upstream of machines related to each other. This study investigates the effect of critical machine reliability improvement on production capacity and throughput time in manufacturing cells. Design/methodology/approach: A discrete-event simulation model was developed to investigate the effectiveness of a reliability plan focusing on the most critical production machines in improving the performance level as an alternative to increasing the reliability of all machines. Four machine criticality policies are examined in the simulation experiments.Findings: The results of this experimental study indicated that an improvement of reliability of a limited number of machines leads to an increase in overall production capacity and speed in cellular manufacturing operations. A reliability plan, that focuses on a set of critical machines, potentially offers a more economical alternative to increasing the reliability of all machines in such facility.Research limitations/implications: The results demonstrate that to achieve higher production capacity and shorter throughput times, managers should consider directing more resources to increase the reliability of critical machines, particularly, those with shorter mean time to failure and higher utilization.Originality/value: The designed simulation model is unique in representing the dynamics of a real world manufacturing cell environment by encoding operational functions such as machine failure, maintenance resource allocation, material flow, job sequencing and scheduling. A new machine availability metric is defined as well.

An Order-Picking Model Associated With Hospital Components and Solved by a Firefly Algorithm

The health industry utilizes critical machines to treat and diagnose illness in patients. Most hospitals cannot afford to have such a machine unavailable; then, they choose to have many components of their critical machines stored inside a warehouse in the hospital. This strategy helps to avoid larger idle times when a machine breaks down. In this chapter, the firefly metaheuristic was selected to solve this problem. This algorithm is related to the behavior of fireflies when they search for potential mating partners. It is also used as a defense against other insects. This behavior consists in the light that they produce. This brightness is the key in this algorithm because, based on this concept, we can use it to attract other fireflies. This characteristic inspired the method to pick components in hospital warehouses.