Performance Analysis of Tyre Manufacturing System in the SMEs Using RAMD Approach

In the recent trends, production plants in the automobile industries all over the world are facing a lot of challenges to achieve better productivity and customer satisfaction due to increasing the passenger’s necessity and demand for transportation. In this direction, the belt, tyre, and tube manufacturing plants act as vital roles in the day-to-day life of the automobile industries. Tyre production plant comprises five major units, namely, raw material selection, preparation, tyre components, finishing, and inspection. The main purpose of this research is to implement the new method to predict the most critical subsystems in the tyre manufacturing system of the rubber industry. As mathematically, any one maintenance parameter among reliability, availability, maintainability, and dependability (RAMD) parameters is evaluated to identify the critical subsystems and their effect on the effectiveness of the tyre production system. In this research, the effect of variation in maintenance indices, RAMD, is measured to identify the critical subsystem of the tyre production system based on the mathematical modeling Markov birth-death approach (MBDA), and the equations of the subsystems are derived by using the Chapman–Kolmogorov method. Besides, it also calculates the performance of certain maintenance parameters concerning time such as mean time between failures (MTBF), mean time to repair (MTTR), and dependability ratio for each subsystem of the tyre production system. Finally, RAMD analysis of the tyre production systems has been executed for predicting the most critical subsystem by changing the rates of failure and repair of individual subsystems with the utilization of MATLAB software. RAMD analysis reveals that the subsystem bias cutting is most critical with the minimum availability of 0.8387, dependability 5.19, dependability ratio 0.8701, and maximum MTTR 38.46 hours of the subsystem. In this implementation of the proposed method, a real-time case study of the industrial repairable system of tyre manufacturing system has been taken for evaluating RAMD indices of the production plant of rubber industry cited in the southern region of Tamil Nadu, India.

Nonlinear Zero-Dynamics Attacks Targeting Nuclear Power Plants

A zero-dynamics attack allows an attacker to input some control action that results in zero measurable output but nonzero response of the internal states. This paper extends previous works on zero-dynamics attacks to nonlinear system dynamics. This is accomplished using invariant subspace techniques that identify the subspace on which zero dynamics exist. An iterative algorithm is presented to identify both this subspace and the resulting zero dynamics of the system. These methods are implemented on a model of a pressurizer in a nuclear power plant, which is a critical subsystem of pressurized water reactors that monitors and controls the system pressure and coolant inventory. This implementation is done by analyzing all combinations of attackable signals. These attackable signals are the set of all system inputs and outputs. From this analysis, there are eight unique combinations of attacked actuators and sensors that result in zero-dynamics attacks. These combinations are characterized by stability and damage time, where damage time is the time it takes to reach some undesirable state. The damage times range from half a day to sixteen days, depending on the number of signals the attacker has access to. These results demonstrate that the physics of the pressurizer system creates some vulnerabilities to zero-dynamics attacks. This work provides plant designers with tools to identify which subsystems are most susceptible to zero-dynamics attacks and might require additional defenses.

Performance modeling and assessment of maintenance priorities for steam generation unit of a sugar plant

Purpose The purpose of this paper is to deal with the performance modeling and assessment of maintenance priorities for steam generation unit of a sugar plant. Design/methodology/approach The unit comprises of four subsystems, i.e., Bagasse elevator, Bagasse carrier, boiler and feed pump. The Chapman–Kolmogorov equations are generated on the basis of transition diagram and further solved recursively to obtain the performance modeling with the help of normalizing condition using the Markov approach. Findings Decision matrices are formed with the help of different combinations of failure and repair rates of all subsystems. The performance of steam generation unit is evaluated in terms of availability levels depicted in decision matrices and plots of failure rates and repair rates of various subsystems. The maintenance priorities of various subsystems of steam generation unit are decided on the basis of effect of failure and repair rates of subsystems on the availability of steam generation unit. The key finding is that the boiler subsystem is the most critical subsystem and hence should be kept on top maintenance priority for performance enhancement of the steam generation unit. Originality/value The acceptance of both performance modeling and maintenance priorities decision by the management of sugar plant will result in the enhancement of unit availability and reduction of maintenance cost.

Maintenance System of Universal Goss Printing Machine based on failure data using RCM and RCS method

OverBased on RCM analysis for each critical subsystem obtained interval preventive maintenance for transfer roller 127.60 hours, Ink fountain roller 24.45 hours, ink form roller 29.23 hours respectively, and the wash-up device is no scheduled maintenance. For spare parts inventory strategies the result using RCS method are: transfer roller104 units, ink fountain roller requires 32 units, ink form roller 36 units and are holding spare policy required, and a wash-up device no holding spare parts. Inserted: r Inserted: u Inserted: ng Inserted: foll Inserted: polic Inserted: d Inserted: the Deleted:in acc Deleted:rdance Deleted:th Deleted:i Deleted: accor Deleted:anc Deleted: with Deleted:strateg

IMPLEMENTATION OF MAINTENANCE SCENARIO FOR CRITICAL SUBSYSTEM IN AIRCRAFT ENGINE Case study: NTP CT7 engine

An aircraft company needs to "secure" their aircraft engine for a good maintenance system to keep the optimum engine's performance during the flight. This paper proposed maintenance analysis and scenario for the CT7, the main engine for aircraft at NTP company. A failure data record from four critical components of the CT7 engine is analyzed using Reliability Centered Maintenance (RCM) and Risk Based Maintenance (RBM) methods to obtain the optimum maintenance interval task for the critical subsystem of the CT7 engine and also seeing the risk of maintenance cost of the engine's failure effect. The RCM analysis result obtained seven scheduled on condition task, six scheduled discard task, and three scheduled restoration task. The interval of the maintenance schedule of each critical component varies according to the function obtained. And based RBM analysis, the risk from system performance loss is got $ 7.014.841, 90. Meanwhile, the total cost of maintenance interval based on a calculation of optimal time interval got $1.885.612, 82. Keywords— preventive maintenance, reliability-centered maintenance, risk-based maintenance, risk priority number.

Simulating R&D decision for critical subsystems in defence R&D projects

Purpose The purpose of this paper is to study the effect of a critical subsystem development indigenously on the outcome of an Indian defence R&D project. Indigenous development of the critical subsystem requires the development of a number of technologies; hence the study is taken up for indigenously development of critical subsystem. Design/methodology/approach A simulation-based approach is used in this paper for studying the effect of indigenization decisions. A defence R&D project with the critical subsystems is modeled in Graphical Evolution and Review Technique (GERT) networks, and simulated in Arena simulation software using discrete event simulation model. The simulation model is thereafter experimented with decision options for the critical subsystem. Data were collected from the project management office (PMO) of short range homing guided missile (SRHGM) for this simulation study. Findings It has been found in this case that timely development of technology plays a key role in the Indian defence R&D projects. While indigenization of critical components reduces cost of development, the trade-off lies in much increased project development time. It is imperative that project teams should identify critical components early and work out appropriate strategies of indigenous development to avoid time overrun of the projects. Research limitations/implications The accuracy of results of the study could perhaps be affected on account of the extent of data forthcoming from the PMO. However, GERT framework presented in this paper is realistically derived from the practices used in the SRHGM project. Originality/value The study would help the project teams to identify critical subsystems early and work out appropriate strategies of indigenous development to avoid time overrun of the projects. This study would also make the project as well as the R&D teams aware of the causes for delays and cost overruns, and assist to deliver a product meeting end-user requirements.

Performance Assessment Based on Reliability of Weaving M251 Machine Using Reliability, Availability & Maintainability (RAM) and Cost of Unreliability (COUR) Methods (Case Study at PT Buana Intan Gemilang)

The textile industry is one of industries that has an important role in the national economy. PT Buana Intan Gemilang (BIG) is one of textile industry in Indonesia which uses Weaving machine to produce motif and sajadah fabrics. The purpose of this research is to analyze the reliability of Weaving M251 machine that has the most damage in 2014. To avoid losses due to machine damage, the reliability, availability and maintainability of the machine need to be improved by using Reliability, Availability & Maintainability (RAM) Analysis method. In addition, the total cost caused by RAM problems can be calculated by using Cost of Unreliability (COUR) method. Based on the evaluation using Reliability Block Diagram (RBD) modeling, it is found that the critical subsystem reliability = 44.36% for 144 working hours and the total repair time that the critical subsystem needs to perform in acceptable operational condition , at least in 1 to 70 hours. There are two different forms of availability that have been calculated, therefore inherent availability = 95,546% which is used as leading indicator, and operational availability = 85,572% which used as lagging indicator. as it is compared, lagging indicator does not meet the performance of leading indicator. The total of unreliability cost when the machine is in active repair time = 39,580,689.02 IDR and within downtime = 135,588,452.13 IDR. Keywords—Cost of Unreliability (COUR), Lagging Indicator, Leading Indicator, Reliability, Availability & Maintainability (RAM) Analysis.

Implementation of Maintenance Scenario for Critical Subsystem In Aircraft Engine: Case Study NTP CT7 Engine

An aircraft company needs to "secure" their aircraft engine for a good maintenance system to keep the optimum engine's performance during the flight. This paper proposed maintenance analysis and scenario for the CT7, the main engine for aircraft at NTP company. A failure data record from four critical components of the CT7 engine is analyzed using Reliability Centered Maintenance (RCM) and Risk Based Maintenance (RBM) methods to obtain the optimum maintenance interval task for the critical subsystem of the CT7 engine and also seeing the risk of maintenance cost of the engine's failure effect. The RCM analysis result obtained seven scheduled on condition task, six scheduled discard task, and three scheduled restoration task. The interval of the maintenance schedule of each critical component varies according to the function obtained. And based RBM analysis, the risk from system performance loss is got $ 7.014.841, 90. Meanwhile, the total cost of maintenance interval based on a calculation of optimal time interval got $1.885.612, 82.