Plant Maintenance Research Articles

About the automation of procedures to assess the operation parameters of by-pass turbojet engines (BTJE)

During aircraft operation, the assessment of operation parameters with the different use of nomograms is completed. This approach is prevalent in the operation of aviation gas-turbine engines as part of aircraft power plants. In this case, for example, the assessment of engine operation parameters on the ground, depending on environmental conditions prior to start-up and run-up, is required. Reducing working hours of the aircraft power plants maintenance can be provided by the automation of the denoted procedures which purpose is the formation of the applicable list of values for assessed parameters while assigning available environmental conditions considering the required restrictions. To allow for the visualization and familiar conceptions of carried out assessments, it is advisable not to be limited to only documenting quantitative parameter estimations but also to provide them with graphical representations. The purpose of the article is not aimed at describing a complete algorithm of the engine operation parameters assessment but demonstrating a solution capability for the automation of the procedures for the engine operation parameters assessment on the ground as the task of search for a solution in the restricted conditions using the approximation 30 apparatus and piecewise approximations by the method of the smallest squares and the correlation criterion of significance. The examples of quantitative estimations for one of mass domestic engines are given. The described approach is applicable to a broad list of engines due to the common character of algorithms for the parameter assessment using nomograms. Software based on the tabular calculation processor from the LibreOffice package, Apache-licensed free software, is cross-platform.

Evaluasi Fungsi Penghijauan pada Median Jalan yang Direndahkan di Jalan Prof. Dr. Ida Bagus Mantra, Bali

Evaluation of the Greening Function at the Lowered Road Median on the Jalan Prof. Dr. Ida Bagus Mantra, Bali. Prof. Dr. Ida Bagus Mantra highway is one of the bypass roads in Bali that was created to avoid congestion on the southern side of the island of Bali. This study aims to evaluate the function of the greening of the lowered median on that road and make recommendations as a solution. The method used was observation with the guidance of assessment criteria to obtain data on the function of a shade, glare barrier, and identity giver. To evaluate the function of aesthetic, the method used was observation and Scenic Beauty Estimation (SBE) questionnaire. The interview method was used to obtain data related to plant maintenance, and literature study method was used to obtain secondary data that support research. The results of this study indicate the shade function gets a good category with an average score of 75.6%, the glare barrier function gets a bad category with an average score of 25.9%, and the identity giver function gets a bad category with an average score of 35, 7%. Assesment of the aesthetic function showed 14 photos of low beauty, 30 of medium beauty, and 4 photos of high beauty were obtained. Recommendations given by researchers in the form of arrangement and maintenance recommendations, where the arrangement recommendations emphasize the addition of the number and type of plants.

The logics and rhetoric of the announced shutdown of the Fessenheim nuclear power plant (France)

AbstractThe closing of the aging nuclear power plant of Fessenheim was eventually concretized in June 2020 after many years of controversy, reflecting the sensibility of closing nuclear power plants in France, the world's second largest producer of nuclear power. This paper provides insight into how this highly policy vexed issue was discussed on the local level during 2017, a period when the decision regarding the shutdown was still at stake. Here, I examine the discursive strategies mobilized by key actors lobbying for the shutdown or maintenance of the nuclear power plant to enhance their argumentations. Using political discourse analyses combined with the logics approach, the article shows that the argumentation of proponents and advocates of a shutdown is structured around the same concept of sustainability. However, economic growth, social prosperity, and environmental “cautiousness” are not articulated with the same chain of equivalence and do not activate the same fantasmatic logics.

Synthetic Dataset of Electroluminescence Images of Photovoltaic Cells by Deep Convolutional Generative Adversarial Networks

Affordable and clean energy is one of the Sustainable Development Goals (SDG). SDG compliance and economic crises have boosted investment in solar energy as an important source of renewable generation. Nevertheless, the complex maintenance of solar plants is behind the increasing trend to use advanced artificial intelligence techniques, which critically depend on big amounts of data. In this work, a model based on Deep Convolutional Generative Adversarial Neural Networks (DCGANs) was trained in order to generate a synthetic dataset made of 10,000 electroluminescence images of photovoltaic cells, which extends a smaller dataset of experimentally acquired images. The energy output of the virtual cells associated with the synthetic dataset is predicted using a Random Forest regression model trained from real IV curves measured on real cells during the image acquisition process. The assessment of the resulting synthetic dataset gives an Inception Score of 2.3 and a Fréchet Inception Distance of 15.8 to the real original images, which ensures the excellent quality of the generated images. The final dataset can thus be later used to improve machine learning algorithms or to analyze patterns of solar cell defects.

Augmented reality with Marker Based Tracking for Introduction to Hydroponics

This research explains the implementation of Augmented Reality (AR) technology with Marker Based Tracking method in the hydroponic recognition system at Pesantren Nurul Huda. This system can assist students in the learning process about the maintenance of hydroponic plants by adding visual and interactive information to the hydroponic plants in the pesantren. In addition, this system can also assist in the management of hydroponic plants by adding features for monitoring the condition of the plants and providing appropriate care recommendations. The results of this research are expected to increase students' interest in agriculture and help in the management of hydroponic plants at Pesantren Nurul Huda. Augmented Reality (AR) can be implemented based on image or picture detection, commonly known as Marker Based Tracking method. By pointing the camera towards the printed image or marker. AR can be applied in 3D hydroponic plant learning system by displaying objects such as types of plants, systems, and growing media. The marker will be detected by the camera and display 3D objects of hydroponic plants, systems, and growing media so that the hydroponic object can be observed in reality. The multimedia development uses Blender and Unity 3D.
 
 Keywords: Augmented realit , Marker Based Tracking, Hydroponics

Adoption of prescriptive analytics for naval vessels risk-based maintenance:A conceptual framework

Prescriptive analytics is a novel maintenance approach by recommending the maintainer, the right maintenance action at the right time through prioritization of maintenance based on the risk. It assists in improving the existing preventive maintenance approach by offering a dynamic maintenance plan based on risk or Risk-based Maintenance Scheduling. To date, there is no clear definition of Naval Vessels Risk-based Maintenance as well as its framework, and it has not been applied extensively in naval vessel maintenance application which is peculiar compared to its application in plant maintenance. This paper reviews Risk-based Maintenance application in industries in an approach to develop prescriptive analytics for a comprehensive and dynamic naval vessels Risk-based Maintenance decision-making framework. It aims to establish an optimal maintenance scheduling to improve naval vessels availability and reduce maintenance costs while meeting stakeholders’ expectations. Objectives and considerations are also defined for peculiarities application of naval vessels. The framework is then evaluated to improve the effectiveness of the current Preventive Maintenance practice and the inconsistency of the existing maintenance decision-making model using the expert judgement in Reliability Centered Maintenance.

Strategi Pengembangan Dan Perluasan Wilayah Pasar Petani Pisang Uli (Musa paradisiaca sapientum)

The study aims to determine the internal and external factors that influence the development of the Banana (Musa paradisiaca sapientum) farming business in Ruguk Village and to formulate an optimal strategy for developing the banana farming business. The analysis used is descriptive analysis, IFE Matrix analysis, EFE Matrix, Internal – External (IE) Matrix, SWOT Diagram, and SWOT analysis. Respondents were selected purposively. The respondents were 8 (eight) experts in their fields. From the results of In the Internal – External (IE) matrix analysis, it was concluded that the farming business should implement a growth strategy, and from SWOT Diagram Analysis since the farming is in quadrant I, they should use an aggressive strategy. Ten specific strategies have resulted from the SWOT analysis, namely the SO strategy: 1). Expanding the scale of banana production, 2) Expanding marketing to supermarkets, and 3) Diversifying processed chip products. WO strategy: 1) Improving the management and the functions of farmer producers cooperative, 2) Providing facilitation and education on diversification of processed products, 3) Utilizing information technology for marketing, communication, and transaction facilities. ST strategy: 1) Improving cultivation management and maintenance to increase the quality and quantity of production. WT strategy: 1) Education on how to handle the disease, 2) Carry out plant maintenance regularly, and 3) Delivery on time.

ADQ—Anomaly Detection and Quantification From Delayed Neutron Monitoring Data of Nuclear Power Plants

Identifying anomalies and quantifying their severity from delayed neutron monitoring data are of great significance to ascertain the reason of anomalous behavior and for predictive maintenance of nuclear power plants (NPPs). An existing anomaly detection technique is primarily aimed to identify anomalies and does not consider quantification of anomalies. In this work, an anomaly detection and quantification (ADQ) technique has been proposed. It detects anomalies based on the fact that abnormal behavior occurs rarely in the real world as opposed to normal behavior. Thereby, the dissimilarity of an anomalous data instance happens to be large from a normal data instance in comparison with dissimilarity between normal data instances and anomalies in itself. This has been exploited by the proposed technique by employing the concept of candidate anomaly pair. It computes a quantified value for severity of given anomaly as intensity in reference to underlying normal behavior, representative of which is extracted from data itself. The proposed technique has been applied on delayed neutron monitoring data of 28 sensors for an NPP, which was provided by Nuclear Power Corporation of India Ltd. (NPCIL), Mumbai, India. The detected anomalies are categorized as point and interval anomalies, and sensors are ranked based on them. The performance of the proposed technique has been found highly promising on validating results with domain experts. The proposed technique has outperformed other three state-of-the-art techniques in terms of anomaly detection rate (ADR), false alarm rate (FAR), and precision.

PENGUATAN LEMBAGA ADAT “KEWANG” DALAM KONSERVASI SUMBER DAYA ALAM DI DESA HARUKU

Kewang is one of the Customary Institutions whose function is to regulate the use and protection of natural resources both on land and at sea. The role of the Kewang Customary Institution in Haruku is maximally related to the function of supervision/controlling of community activities convert the mangrove forest ecosystem which is the lompa fish habitat. In addition to the activities of the people who hunt and take eggs from scorched birds freely. The goals to be achieved from Community Service activities carried out in Haruku country are 1. Rehabilitation of mangrove forest ecosystems as lompa fish (Trisina baelama) habitat, 2. Improving partners' abilities and skills in carrying out mangrove cultivation techniques, 3. Increasing partner supervision on the presence/population of gosling birds. The method used to transfer science and technology is 1). Preparation, 2). The implementation stage consists of: counseling and training, procuring mangrove seeds/saplings and making nurseries, planting, making scorched bird breeding cages, carrying out maintenance of mangrove plants that have been planted in the field and at the nursery location. The results achieved in this activity were making nurseries and planting 1000 mangrove saplings, building 2 bird brooding cages, cleaning the beach, counseling on mangrove cultivation and nursery techniques, the Role of Indigenous Institutions in the Management of Natural Resources, Breeding of rare fauna.

Heat Rate Deviation Analysis of a Coal-Fired Power Plant (CFPP) with the Influence of Applicable Coal Prices (ACP)

The assessment of a Coal-Fired Power Plant (CFPP) performance is an intricate process that involves the determination of Heat Rate (HR) deviations of current operational parameters from baseline or target values. This study focuses on HR deviations of a CFPP based on the Applicable Coal Price (ACP), and the influence of the ACP price on daily losses or gains are thoroughly analyzed for key performance parameters for three fixed ACP of RM12, 18, and 24 per GJ. This paper mainly investigates key parameters and related equipment that significantly affect the HR of the CFPP and ranks the parameters affecting HR from most significant to least significant. The baseline or target values are obtained from the plant commissioning manuals and the Performance Guarantee Test (PGT). Actual real-life operational data from a 700MWn CFPP is utilized to improve the accuracy and confidence levels of the results obtained. It was found that at the nominal operating baseload, the most significant negative HR deviation is for the Rotary Air Heater (RAH) gas exit temperature with a negative HR deviation of -137.9 kJ/kWh leading to an annual loss of RM17.6 million at ACP of RM24/GJ while the superheater and reheater spray flows are contributing least to the HR deviation. This analysis highlighting the impact of key parameters affecting the performance enables plant operations and maintenance teams to focus on such parameters to mitigate losses.

Prototype Sistem Monitoring Intensitas Cahaya pada Budidaya Tanaman Cabai Rawit dengan Konsep Smart Farming Berbasis Internet Of Things (IOT)

Light intensity is an important factor to consider as best as possible to support plant fertility and health, especially in cayenne pepper plants. One of the innovations that can be applied to assist the management and maintenance of plants in Greenouse is agricultural technology based on the Internet of Things (IoT) or called smart sarming. In the use of Smart farming technology, the process of Monitoring crop needs is carried out by sensors and microcontrollers so that farmers can monitor all data in real time. This final project aims to describe the implementation of a light intensity Monitoring system in an IoT-based Greenhouse and produce a light intensity Monitoring tool in a Greenhouse using an LDR sensor so that farmers can know that the plants are getting an adequate supply of light. The smart farming system is designed using the MQTT (Message Queue Telemetry Transport) protocol as the center for transferring and receiving data from sensors to Monitoring applications. The stages of implementing system into the Greenhouse include: (1) installation of sensors and microcontrollers on the Prototype Greenhouse for cayenne pepper cultivation; (2) design and decision-making to be carried out by the system; (3) create web and android applications as a place for Monitoring data by end users. The results show that the light intensity Monitoring system in cayenne pepper cultivation is based on the Internet Of Things (IoT), include: first, the manufacture of a system Monitoring tool whose light intensity is carried out in 4 steps, namely determining the components, assembling of components into a series of Monitoring systems, programming toolkits and application software, and packaging step. And the second, the implementation of the light intensity Monitoring system in cayenne pepper cultivation includes the system trial stage which produces an average value of 2676 LUX or 62.43% on sensor readings 12 times over a period of 3 minutes it is still at the optimal level for the growth of cayenne pepper plants with a minimum intensity value of 2528 or 50%. The output value calibration results on the Monitoring application with the LUX Meter application show the same and accurate value. So, it can be concluded that the IoT-based light intensity Monitoring system can run well and can be implemented for Greenhouse farming of cayenne pepper.

Building the Creativity of Bulurejo Village Community through the TASAPOT Cultivation in the Pandemic Era

Bulurejo Village is one of the villages in Gadingrejo Subdistrict, Pringsewu Regency, Lampung Province. Bulurejo Village has a quite active Women Farmer Group (Kelompok Wanita Tani/ KWT) known as ‘Ayu Tani’, which was formed in 2014 with 27 members. Bulurejo Village is one of the villages that has the potential to develop the cultivation program of potted vegetable plants (Tanaman Sayur Dalam Pot: TASAPOT). TASAPOT cultivation is conducted to increase the consumption of various food sources in the form of vegetables with the principles of being nutritious, balanced, diverse, and healthy, so that organic farming can be applied during a pandemic era with the aim of increasing body immunity. This community services program aims to equip the community of Bulurejo Village with theoretical and practical knowledges regarding the cultivation techniques of vegetable plants in pots. The method used includes extension, discussion, mentoring, and training or direct practice in the field based on the initial evaluation as a basis for determining the knowledge level of the target partner's regarding the cultivation techniques of TASAPOT. The implementation of this community services program has succeeded to achieve the expected outcomes, namely increased knowledge of the community and members of the 'Ayu Tani' KWT in Bulurejo Village about the importance of Sustainable Food Houses (Rumah Pangan Lestari: RPL) and the cultivation techniques of TASAPOT to improve family’s health the community's standard of living. In addition, there has been an increase in partners’ understanding of the cultivation techniques of TASAPOT, starting from the benefits of utilizing the house yard, the growing media used, planting techniques, and plant maintenance until harvest.

Performance Evaluation of Wastewater Treatment plant, Vidyaranyapuram, Mysuru

Background: The primary goal of sewage water treatment is to eliminate or bring down the number of pollutants in the sewage water. This study was needed to assess the efficacy of a sewage treatment plant in reducing contaminants levels to comply with government environmental standards. The wastewater re-use for irrigation approaches must be in compliance with the guidelines and indicators must be tracked and impended consistently, it is therefore essential to give top priority to requirements at the stage of evaluating and development to protect land and water supplies as well as public health. Methods: Chemical and biological approaches were used to regulate the removal efficiency of treatment plants. The performance and effectualness of the Vidyaranyapuram sewage treatment plant (STP) in Mysore are evaluated and analyzed in this report. Novelty: Water quality needs to be regularly checked in wastewater treatment facilities. The current study will aid the treatment facility in its efforts to enhance the process of treatment. One would be able to update the effluent efficiency levels depending on the seasonal variations in wastewater treatment as the assessment explains the number of water quality metrics in waste water plants. The obtained analysis results are very helpful in locating, fixing, and maintaining plant operating and maintenance issues, which may be helpful for next plant expansion to be carried out to get good results. Result: The STP's treatment efficiencies were discovered to have a good treatment level in BOD (96%) and a moderate treatment quality in COD (79%) and TSS (75%) removal efficiency during the year 2018. Conclusion: To ensure correct operation and maintenance, trained and experienced workers must analyze treatment performance at predetermined time intervals. The result explains the quality of effluent water and performance of treatment plant. STPs should be used to their full potential to manage the quality of final effluent, and raw sewage sources should be identified.

Handling Type-I and Type-II endogenous uncertainties in simultaneous production planning and condition-based maintenance optimization in continuous production

This work proposes a novel stochastic programming formulation that can handle Type-I and Type-II endogenous uncertainties with the goal of simultaneously optimize production planning and condition-based maintenance of continuous production plants. A degradation model that is able to predict the Remaining Useful Life of the equipment is embedded into the optimization problem and we consider this prediction to be uncertain. Each scenario of the stochastic program represents an uncertain realization of the predicted Remaining Useful Life and has a certain probability of realization. These probabilities can be altered by the decision maker, thus rendering some predictions more likely than the others by acting on the utilization of the plant (Type-I endogenous uncertainty). The maintenance activities recover the health of the equipment and the decisions on maintenance make some scenarios not realize any more and, therefore, modify the structure of the scenario-tree (Type-II endogenous uncertainty). We present two different modelling approaches for this novel class of stochastic programs based on superstructure scenario trees and on conditional non-anticipativity constraints. For a simple generic example, we analyse the influence of the modelling approach on the computational time that is needed to solve the resulting MINLP problem with the global solver BARON. We also investigate several branching priority strategies to reduce the computational effort for this class of problems. We demonstrate the advantages that can be achieved using the proposed formulation compared to the deterministic counterpart.This work sets the ground for modelling and solving simultaneous production planning and condition-based maintenance problems. To deal with larger-scale industrial problems, additional work is required to develop custom solution techniques to reduce the computational burden.

The Effectiveness of Giving Various Planting Media to the Floating Raft Aquaponics System on the Growth of Shallots

Aquaponics consists of fish farming and plant maintenance. Water, which is a medium for fish cultivation, is used as a source of nutrition in plant maintenance, while plants function as a biofilter for water. This study used red onion seeds of the Sanren variety. This study was an experimental study using a non-factorial randomized block design (RBD) consisting of 1 treatment factor and 5 blocks. to get 20 research plots. Planting Media Factor with a symbol (M) which consists of 4 levels, namely: M1: Compost, M2: Chaff Charcoal, M3: Cocopeat, M4: Rice Husk. The results showed that the use of several growing media in the floating raft aquaponic system had a very significant effect on plant height (cm) and the number of leaves (strands).

SPECIES COMPOSITION, STRUCTURE, AND MANAGEMENT IN GAYO COFFEE-BASED AGROFORESTRY SYSTEM

Gayo coffee has many benefits in terms of the environment, economy, and socio-cultural aspects, especially for the Gayo tribe. Recently, Gayo coffee has been the main commodity for the plant cultivation of the Gayo tribe, including the Mude Nosar as local farmers. One of the ways to cultivate Gayo coffee is through an agroforestry system. However, limited reports on the tree species composition and its management in Gayo coffee-based agroforestry needs to be explored. This study aims i) to identify the tree species composition and structure, as well as 2) to analyze the management of Gayo coffee-based agroforestry system in Mude Nosar Village. The study method used plot establishment for vegetation analysis, and interviewed the Gayo coffee farmers. The results showed that the number of tree species at all growth stages was 26 species. The highest Important Value Index (IVI) at the understory and sapling level in order was rumput kerbau (Paspalum conjugatum) and Gayo coffee (Coffea arabica), while at the seedling, pole, and tree levels were dominated by lamtoro (Leucaena leucocephala). The local farmers often use lamtoro as a shade tree for Gayo coffee in agroforestry system. The species diversity index (H') showed low values at all growth levels, except for understory plants with moderate values. The horizontal structure of the tree stand showed an inverted J curve, meaning that the regeneration rate is normal. The vertical structure of the tree stand belongs to strata C and D. The local farmers have applied good Gayo coffee management practices through an agroforestry system including land and seed preparation, planting, maintenance, and harvesting techniques. Coffee seeds and seedlings are from natural regeneration. Plant maintenance techniques are carried out by weeding, pruning, organic fertilization, and controlling pests and diseases. The harvest coffee season is generally twice a year. The management of Gayo coffee using an agroforestry system impacts the ecological, economic, and social aspects.

IoT based solar panel fault and maintenance detection using decision tree with light gradient boosting

Solar PV (photovoltaic) technology has advanced greatly in recent years due to advantages such as renewability, environmental friendliness, simple maintenance, and dependability. Nevertheless, a number of PV faults may appear and result in degradation, a decrease in output power, or even a storm surge at different levels, depending on the outside working conditions and regular weather changes that might cause harm to the production, distribution, or setup, it is critical to monitor PVSs (PV systems) for their power generation efficiencies. IoT (Internet of Things) are evolving technologies that have been studied for enhanced fault detection and predictive analysis in the maintenance and environmental monitoring of solar power plants. This research work suggests a method based on MLTs (machine learning techniques) to analyze power data and predict faults for the maintenance of solar power plants. Input data from solar power plants consist of plant power generation and weather data which are first pre-processed and then trained using the suggested DT-LGB (Decision Trees with Light Gradient Boosting) algorithm to predict errors. The trained model was able to identify major/minor faults or anomalies present in input data. Conventionally these identifications require more effort in detection and maintenance. The results of this work showed that the suggested model obtained 8.74 MSEs ((Mean Square Errors), 2.96 RMSEs (Root Mean Square Errors), and R2 values of 0.9939 which is 12.8%, 6.8%, and 11.08% improved than the existing method respectively.

Cyclin A participates in the TSO1-MYB3R1 regulatory module to maintain shoot meristem size and fertility in Arabidopsis.

The stem cell pools at the shoot apex and root tip give rise to all the above- and below-ground tissues of a plant. Previous studies in Arabidopsis identified a TSO1-MYB3R1 transcriptional module that controls the number and size of the stem cell pools at the shoot apex and root tip. As TSO1 and MYB3R1 are homologous to components of an animal cell cycle regulatory complex, DREAM, Arabidopsis mutants of TSO1 and MYB3R1 provide valuable tools for investigations into the link between cell cycle regulation and stem cell maintenance in plants. In this study, an Arabidopsis cyclin A gene, CYCA3;4, was identified as a member of the TSO1-MYB3R1 regulatory module and cyca3;4 mutations suppressed the tso1-1 mutant phenotype specifically in the shoot. The work reveals how the TSO1-MYB3R1 module is integrated with the cell cycle machinery to control cell division at the shoot meristem.

X-ray Computed Tomography for Nuclear Power Plant Maintenance

As part of the scheduled maintenance of nuclear power plants, specialist tools are deployed into the reactor core, for example to inspect the moderator. It is imperative that these tools operate correctly, and that no element of the tool remains in the reactor when the reactor resumes operation. The current processes for ensuring this are hugely labour intensive, and hence costly, involving a full teardown before and after deployment. This paper describes the development of a novel X-ray Computed Tomography (CT) system and workflow for ensuring the integrity of specialist reactor tools without the need for disassembly. The system hardware must be able to deal with the challenge of tools that are up to 6 metres in length and contain a significant amount of dense componentry. On the other hand, the system software must be able to confirm the correct and comprehensive assembly of the tool based on the obtained CT scan, and despite numerous potential, but benign, differences in the tool appearance. The presented approach overcomes both challenges: the hardware uses a gantry design with a high-powered X-ray source (see Fig. 1), the software employs a machine learning implementation.

Statistical Test-Based Practical Methods for Detection and Quantification of Stiction in Control Valves

Control valve, affected by stiction, causes closed-loop signals to experience oscillations, which ultimately leads to a decrease in product quality, reduced plant throughput, and increased environmental footprint. Therefore, it is indispensable to detect and quantify stiction in control valves. To accomplish this objective, in the present work, four noninvasive practical and simple methods are developed with the help of statistical tests such as F-test, t-test (Student’s t-test), modified Hotelling T2-test, and reverse arrangement test (RAT). The developed methods are applied to benchmark control loops espoused from chemical, paper, and mining industries. The results of the proposed methods are compared with that of existing methods found in the literature. It is found that the t-test-based method, the modified Hotelling T2-test-based method, and the RAT-based method demonstrate equally good or better performance than the existing methods, while the F-test-based method outperforms some of the existing methods. In addition to detecting stiction, the proposed methods can quantify stiction to timely notify panel operators of stiction severity and assist plant maintenance engineers to arrange plant shutdowns well ahead in time. The proposed methods are applicable to all types of control loops except level loops.