Performance Assessment Process Research Articles

Machining Performance Optimization for Turning of Inconel 825: An integrated Optimization Route Combining Grey Relation Analysis with JAYA and TLBO

With the widespread application of Inconel alloys in manufacturing industries especially in the automobile as well as aerospace industries leads to manufacturers to pay more attention towards the understanding of machinability aspects of these alloys. Attributable to the need for large-scale manufacturing of Inconel machined components, the optimization of machining process variables become crucial to produce quality products economically by means of enhancing process performance. In common, several process parameters namely depth of cut, feed rate, and spindle speed influence the performance of turning operation in their own way. Concurrently, in the machining of Inconel alloys, the important performance indices are Material Removal Rate (MRR), surface roughness, and cutting force. This work deals with the assessment of process performance of Inconel 825 alloy amid turning operation. For the optimization of multiple responses, grey relation analysis has been employed that transforms the multiple responses into a corresponding single response known as overall grey relation index (OGI). Based on OGI, as a function of selected process variables, formulation of a non-linear regression model has been done and considered as the fitness function. To conclude, two evolutionary techniques, Teaching-Learning-Based Optimization, well famous as TLBO, and JAYA algorithm have been considered for optimization.

Performance-relevant kernel independent component analysis based operating performance assessment for nonlinear and non-Gaussian industrial processes

The operating performance assessment of industrial processes becomes increasingly important in manufacturing production. A novel operating performance assessment method based on performance-relevant kernel independent component analysis is proposed here for nonlinear and non-Gaussian processes. The proposed method accounts for the comprehensive economic index, and the objectives are simultaneously to maximize the non-Gaussianity of independent components as well as the correlations between them and the comprehensive economic index. When applying it to online assessment, it demonstrates stronger robustness and higher sensitivity than the traditional methods do, which is attributed to its capacity in highlighting the performance-relevant variation information in modeling. Furthermore, both the performance grades and the conversions can be evaluated, which enhances the interpretability of the results. For the nonoptimality, the variable contributions are used to find the possible cause. Finally, the efficiency of the proposed method is illustrated by a case of gold hydrometallurgy process.

Automated Change Detection: Applications for Synthetic Aperture Sonar and Future Capabilities

We present an overview of an automated end-to-end change-detection process as it is applied to synthetic aperture sonar (SAS) imagery. Although we are discussing an example of a single application, the automated change-detection (ACD) process can be applied to different imaging modalities, such as medical imaging, synthetic aperture radar (SAR), remote sensing, and radio astronomy. This article introduces the different processing steps of the automation: image coregistration, change-map generation, detection, and data reduction (false-alarm reduction) as it applies to automatic target recognition using sonar imagery. We examine ACD applications to multitemporal SAS imagery in detecting changes on the sea floor. In addition, we discuss some of the challenges and necessary approaches to augment the ACD process for operator decision-aid tools and performance assessment of the process.

A New Fuzzy Based Marketing Performance Measurement Model with a Real Case Study

The level of efficiency for business and process control is based on performance measurements. Performance measurement is a mixed system that contains many different criteria such as customer behaviour, sales, employees and product range. Businesses need to measure sales performance to maintain sustainable competition lines and improve their strategies. In this paper, a performance measurement in the clothing industry has been carried out and a pioneering company data has been utilized as the application area. In the paper, Interval Valued Pythagorean Fuzzy Analytical Hierarchy Process (IV-PFAHP) method and Interval Valued Pythagorean Fuzzy TOPSIS (IV-PFTOPSIS) method have been suggested to deal with marketing performance assessment process with a real case study. The paper focuses on IV-PFAHP and IV-PFTOPSIS methods to handle uncertainty in the marketing performance assessment process for clothing industry. The results revealed that the proposed approach produces reliable outcomes representing the vagueness of the decision-making process.

Construction and fuzzy hypothesis testing of Taguchi Six Sigma quality index

By taking process targeting as well as process variability into consideration, the Taguchi capability index gives a reasonable indication of process loss. This makes it an ideal tool for practical applications that depend on the evaluation of process quality. The ability of Six Sigma quality management to reduce process defect rates has led a number of researchers to investigate the relationship between and Six Sigma quality levels. Unfortunately, previous efforts indicate the quality level using only a range, rather than a specific value. Our objective in this study was to develop a Taguchi Six Sigma quality index that retains the advantages of in the assessment of process performance, while providing a specific value for the quality level associated with the process in question. To ensure rigorous quality assessments, we employed the upper confidence limit of in the design of a testing model for use by manufacturers. Fuzziness and stochastic uncertainty are unavoidable aspects of data collection. We, therefore, adopted a right half triangular-shaped fuzzy number for to deal with imprecise data. We also developed a method of the fuzzy hypothesis testing for to make reliable decisions for process quality assessment.

Advancements on scaling-up simulation of Proton Exchange Membrane Fuel Cells impedance through Buckingham Pi theorem

This article addresses a generalized scaling-up technique applied to proton exchange membrane fuel cells. Such a methodology allows simulating the impedance related to a full stack from that of a single cell or short stack, combining experimental data with physical reasoning and phenomenological modelling. The use of such technique can reduce electrochemical impedance spectroscopy testing costs, with a significant impact on fuel cell manufacturing and performance assessment processes. The procedure described in this paper relies on a former approach, already presented by the authors, which has been improved with respect to two main aspects. Firstly, non-dimensional parameters are computed, by referring to the Buckingham Pi theorem, through a generalized physical model. Secondly, single cell or short stack internal states (i.e., water content and limiting current) are evaluated through significant information gained from impedance measurements and inverse modelling. Stack impedance simulation is performed through proper internal states distribution assumptions. To prove the consistency and robustness of the proposed technique, experimental data taken from the literature and the European funded project HEALTH-CODE are used, with stack impedance accurately reproduced by means of only a single cell spectrum.

PENERAPAN DATA MINING DALAM PENILAIAN KINERJA GURU TETAP SD NEGERI KEBALEN 07 DENGAN METODE TOPSIS

To find out the problems faced in the teaching performance assessment process by utilizing the Technique For Order Preference method by Similiarity to Ideal Solution (TOPSIS), to manage the processing of Teacher data is a more optimal consideration. By using the (TOPSIS) method as a basis for processing teacher performance assessment data. This can allow the system to provide an assessment in accordance with the quality of each teacher and is expected to facilitate decision making in the assessment of Teacher's performance. The Technique For Order Preference by similiarity to Ideal Solution has been running well and can result in a weighting of assessment criteria and clear and fast information compared to manual calculations so SD Negeri Kebalen 07 can use it as a tool for making appropriate decisions.

PERFORMANCE INDICATORS FOR ENERGY EFFICIENCY RETROFITTING IN MULTIFAMILY RESIDENTIAL BUILDINGS

ABSTRACT The energy performance of an existing building is the amount of energy consumed to meet various needs associated with the standardized use of a building and is reflected in one or more indicators known as Building Energy Performance Indicators (EnPIs). These indicators are distributed amongst six main factors influencing energy consumption: climate, building envelope, building services and energy systems, building operation and maintenance, occupants' activities and behaviour, and indoor environmental quality. Any improvement made to either the existing structure or the physical and operational upgrade of a building system that enhances energy performance is considered an energy efficiency retrofit. The main goal of this research is to support the implementation of multifamily residential building energy retrofits through expert knowledge consensus on EnPIs for energy efficiency retrofit planning. The research methodology consists of a comprehensive literature review which has identified 35 EnPIs for assessing performance of existing residential buildings, followed by a ranking questionnaire survey of experts in the built-environment to arrive at a priority listing of indicators based on mean rank. This was followed by concordance analysis and measure of standard deviation. A total of 280 experts were contacted globally for the survey, and 106 completed responses were received resulting in a 37.85% response rate. The respondents were divided into two groups for analysis: academician/researchers and industry practitioners. The primary outcome of the research is a priority listing of EnPIs based on the quantitative data from the knowledge-base of experts from these two groups. It is the outcome of their perceptions of retrofitting factors and corresponding indicators. A retrofit strategy consists of five phases for retrofitting planning in which the second phase comprises an energy audit and performance assessment and diagnostics. This research substantiates the performance assessment process through the identification of EnPIs.

In Situ Additive Manufacturing Process Monitoring With an Acoustic Technique: Clustering Performance Evaluation Using K-Means Algorithm

Additive manufacturing (AM) is based on layer-by-layer addition of materials. It gives design flexibility and potential to decrease costs and manufacturing lead time. Because the AM process involves incremental deposition of materials, it provides unique opportunities to investigate the material quality as it is deposited. Development of in situ monitoring methodologies is a vital part of the assessment of process performance and understanding of defects formation. In situ process monitoring provides the capability for early detection of process faults and defects. Due to the sensitivity of AM processes to different factors such as laser and material properties, any changes in aspects of the process can potentially have an impact on the part quality. As a result, in-process monitoring of AM is crucial to assure the quality, integrity, and safety of AM parts. There are various sensors and techniques that have been used for in situ process monitoring. In this work, acoustic signatures were used for in situ monitoring of the metal direct energy deposition (DED) AM process operating under different process conditions. Correlations were demonstrated between metrics and various process conditions. Demonstrated correlation between the acoustic signatures and the manufacturing process conditions shows the capability of acoustic technique for in situ monitoring of the additive manufacturing process. To identify the different process conditions, a new approach of K-means statistical clustering algorithm is used for the classification of different process conditions, and quantitative evaluation of the classification performance in terms of cohesion and isolation of the clusters. The identified acoustic signatures, quantitative clustering approach, and the achieved classification efficiency demonstrate potential for use in in situ acoustic monitoring and quality control for the additive manufacturing process.

Using multivariate pattern segmentation to assess process performance and mine good operation conditions for dynamic chemical industry

Before performing any in-depth analytics, an important issue in dealing with historical dynamic data is to extract data segments from the operation data. The raw data always involve different kinds of patterns over a long series of sequences because of the operation changes or some faults. Conventional methods for identifying the patterns are based on variance or covariance, but the indices designed from variance or covariance are not necessarily able to cover the process dynamics completely, so the precision degradation of segmentations will be induced. This paper designs a new dissimilarity index based on the autocorrelation function to deal with dynamic data. And a fast and high-efficient segmentation algorithm using interval halving and the moving window is proposed to locate the change points of data patterns. Moreover, a new dynamic performance assessment index is designed to find the optimal segment in the dataset. Two case studies, including a numerical example and a distillation column benchmark, validate the advantages of the proposed scheme over the conventional variance-based methods.

Practicality of Performance Assessment Instruments in Measurement Topic 10th Grade Secondary School

One of the competencies in Curriculum 2013 is having the skills to apply knowledge in doing scientific inquiry, while the skills are divided into two kinds: concrete and Achievement of these competencies can be determined by assessment. The information of student’s ability given by authentic assessment is believed to be more holistic and valid, one of them is performance assessment. It is conducted to assess how appropriate the students in completing their tasks in the form of action or deed. The aim of this research is to obtain a description of the practicality and percentage of agreement of performance assessment instruments on measurement topic for 10th grade secondary school. This research subject of trial as many as 19 students in 10th science class at SMA Muhammadiyah 2 Surabaya with trial design one group pre-test post-test. Data are collected by using observation and direct questionnaire methods. The results showed that the practicality of the instrument based on the implementation of the assessment and the results of student responses fulfills the practical criteria and agreement between observers on the implementation of product performance assessment and process performance assessment are well categorised.

Optimal Performance of Caps’ Pressing Process Using Taguchi-Grey Method

This paper aims at improving the performance of caps’ pressing process using Taguchi-grey relational analysis. Five main quality characteristics were considered, involving cap’s height, inner diameter, outer diameter, angle, and plastic weight. The individual and moving range control charts were constructed for each quality characteristic. Then, process capability analysis was then carried out to assess process performance at initial process factor settings, at which the process was found incapable in producing conforming caps for some quality characteristics. Thus, the Taguchi’s designed experiments were employed to provide experimental layout followed by the grey relational analysis to determine the combination of optimal factor settings. Results showed significant in almost all the five quality responses and thereby resulted in huge production and quality cost savings. 

Decision Support Systems Selection Of The Best Teachers With The Composite Performance Index Method Approach

The development of Information Technology has a huge impact on various aspects of life, ranging from government, administration, economics, and education. Regarding the issue of education in particular, the use of information technology will bring very good changes in the education system that will be developed to be delivered. With the existence of computer technology as a support in the transmission of data and information has become the needs of all humans, so that information information needed can be obtained quickly and accurately. In fact, one of the most important factors in the problem of information technology is network problems or media access that become a bridge between learning resources and those involved in the learning process. The Teacher Performance Assessment process in the Composite Performance index (CPI) method is very good in developing the level of knowledge in ordinary people, so that the utilization of information technology can be maximally useful at every level of society.

Process performance and life cycle assessment of friction drilling on dual-phase steel

The use of friction drilling technique for hole making in tube dual phase steels was presented in this paper as an alternative to conventional drilling techniques. Due to the higher environmental consciousness growing up in the last years in different industrial environments, the feasibility of the proposed alternative must be analyzed taking into account both, technical and environmental aspects. In order to perform a complete environmental approach for conventional drilling, different lubri-cooling technologies were tested: dry drilling, wet drilling and minimum quantity of lubrication (MQL) drilling using high-oleic sunflower oil. From the technical point of view, results show that using friction drilling, the surface quality obtained was more appropriate. The deformed material provides a perfect base for future threading or joining operations and, moreover, the thermal affected layer observed in micrographies provides a 20 μm hardened layer which reduce surface wear and damages, improving hole zone life. From the environmental point of view, a life cycle assessment (LCA) was carried out for both drilling techniques and different lubricooling environments. Results show that friction drilling presents an ecologic improvement, obtaining a notable reduction in all impact categories. Analyzing both points of view, friction drilling is presented as a solution that improves current drilling processes of metal sheets.

Comparative performance assessment of flat sheet and hollow fiber DCMD processes using CFD modeling

The effects of select system parameters on the performance of direct contact membrane distillation (DCMD), in terms of permeate flux (J) and temperature polarization coefficient (TPC), were investigated and compared for flat-sheet (FS) and hollow-fiber (HF) modules. Three-dimensional (3D) computational fluid dynamics (CFD) models were developed and validated using experimental data. Then, a two-level full factorial design tool was used to design the simulation runs to investigate the effects of four selected process parameters on flux and TPC. These are: feed inlet temperature (Tf), permeate inlet temperature (Tp) and Reynolds number on the feed (Ref) and permeate (Rep) sides. The effect of each factor and the interactions thereof were assessed based on data obtained from the CFD models.Although all four parameters showed a significant influence on flux and TPC, their interactions had different effects on the HF and FS modules. For instance, since the permeate stream temperature increases much faster along the permeate channel in the HF module than in the FS module, Rep has a more substantial impact in the HF module. At higher Rep values, higher Tf results in further enhancement in permeate flux in the HF module. Furthermore, the CFD model results indicate that the FS module generally showed better performance, in terms of permeate flux, than the HF module under the same DCMD process conditions. In the CFD model runs which yielded the highest flux in both HF and FS modules, the permeate outlet temperatures from the HF and FS modules were 21.72 °C and 18.53 °C, respectively, under the same operating conditions. Generally, the HF module exhibited about 21% lower flux than the FS module.

PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images.

Grand challenges stimulate advances within the medical imaging research community; within a competitive yet friendly environment, they allow for a direct comparison of algorithms through a well-defined, centralized infrastructure. The tasks of the two-part PROSTATEx Challenges (the PROSTATEx Challenge and the PROSTATEx-2 Challenge) are (1)the computerized classification of clinically significant prostate lesions and (2)the computerized determination of Gleason Grade Group in prostate cancer, both based on multiparametric magnetic resonance images. The challenges incorporate well-vetted cases for training and testing, a centralized performance assessment process to evaluate results, and an established infrastructure for case dissemination, communication, and result submission. In the PROSTATEx Challenge, 32 groups apply their computerized methods (71 methods total) to 208 prostate lesions in the test set. The area under the receiver operating characteristic curve for these methods in the task of differentiating between lesions that are and are not clinically significant ranged from 0.45 to 0.87; statistically significant differences in performance among the top-performing methods, however, are not observed. In the PROSTATEx-2 Challenge, 21 groups apply their computerized methods (43 methods total) to 70 prostate lesions in the test set. When compared with the reference standard, the quadratic-weighted kappa values for these methods in the task of assigning a five-point Gleason Grade Group to each lesion range from to 0.27; superiority to random guessing can be established for only two methods. When approached with a sense of commitment and scientific rigor, challenges foster interest in the designated task and encourage innovation in the field.

Hierarchical Multiblock T-PLS Based Operating Performance Assessment for Plant-Wide Processes

With the pursuit of profit, the operating performance assessment of industrial processes has gradually attracted attention and concentration in modern industrial production. However, owing to the complexity of plant-wide processes, many existing operating performance assessment techniques are lacking in interpretation of the assessment result, and the cause identification is also difficult for the nonoptimal operating performance. In this study, a new operating performance assessment method is proposed for plant-wide processes based on hierarchical multiblock total projection to latent structures (T-PLS). The proposed approach divides the process variables into several conceptually meaningful blocks and incorporates block information into high level for operating performance assessment of plant-wide processes. With the new method, the assessment task can be greatly reduced and the interpretability of the assessment models are greatly improved. Once the process operating performance is nonoptimal, the resp...

Assessment of micellar-enhanced ultrafiltration process performance for removal of pharmaceutical contaminant from wastewater using response surface methodology

In the present research, removal of a common pharmaceutical contaminant from wastewater was studied using micellar-enhanced ultrafiltration (MEUF) process with applying a laboratory-scale system. Sodium dodecyl sulfate surfactant was used in this process. Response surface methodology (RSM) was applied for evaluating the MEUF process performance. The results obtained from the experiments showed that sotalol hydrochloride drug rejection using ultrafiltration membrane was maximum 32.41%, while by adding the surfactant and forming the micelle this amount increased to 96.82%. By using the RSM and investigating the interaction of surfactant concentration, transmembrane pressure (TMP), and pH, it was found that the surfactant concentration had the most impact on the rejection. Moreover, among the studied parameters, TMP and surfactant concentration played an important role in variations of the permeate flux.

Analysis of process intensification and performance assessment for fermentative continuous production of bioethanol in a multi-staged membrane-integrated bioreactor system

The work analyses process intensification in production of fermentative biofuel (bioethanol) in a multi-staged membrane integrated bioreactor system from sugarcane juice (SCJ) using Saccharomyces cerevisiae (NCIM 3205). Membrane based clarification, sterilization and concentration of sugar cane juice could replace several energy-intensive and polluting steps of conventional production schemes. Integration of traditional bioreactor with membrane-based devices for downstream purification of bioethanol enabled the system for recycling of cells and residual sugars to the fermentation unit through largely fouling free cross flow microfiltration and nanofiltration membrane modules. The new process design is characterized by high yield (0.48 g/g), productivity (14.6 g/L/h) and concentration capability (97.6 g/L) using concentrated SCJ of 22 wt% under high cell density in a flexible, compact, eco-friendly and modular plant. The final membrane distillation stage concentrated ∼98% pure ethanol in a solar-driven direct contact membrane distillation configuration using PTFE/PET hydrophobic membrane with enhanced flux with vis-à-vis the existing processes. A rectangular flat sheet cross flow membrane module in counter-current flow mode of hot and cold streams was employed. The membrane-based system achieves quite high levels of process intensification essential to sustainable operation at industrial scale. The achieved process intensification in the new system has been analysed vis-a-vis the existing conventional systems in terms of eco-friendliness, flexibility, cost of equipment and production, consumption of energy and material, profitability, E-factor, atom efficiency and business sustainability.

Communicable Disease Surveillance Systems in Disasters: Application of the Input, Process, Product, and Outcome Framework for Performance Assessment.

One of the most important measures following disasters is setting up a communicable disease surveillance system (CDSS). This study aimed to develop indicators to assess the performance of CDSSs in disasters. In this 3-phase study, firstly a qualitative study was conducted through in-depth, semistructured interviews with experts on health in disasters and emergencies, health services managers, and communicable diseases center specialists. The interviews were analyzed, and CDSS performance assessment (PA) indicators were extracted. The appropriateness of these indicators was examined through a questionnaire administered to experts and heads of communicable diseases departments of medical sciences universities. Finally, the designed indicators were weighted using the analytic hierarchy process approach and Expert Choice software. In this study, 51 indicators were designed, of which 10 were related to the input (19.61%), 17 to the process (33.33%), 13 to the product (25.49%), and 11 to the outcome (21.57%). In weighting, the maximum score was that of input (49.1), and the scores of the process, product, and outcome were 31.4, 12.7, and 6.8, respectively. Through 3 different phases, PA indicators for 4 phases of a chain of results were developed. The authors believe that these PA indicators can assess the system's performance and its achievements in response to disasters. (Disaster Med Public Health Preparedness. 2019;13:158-164).