Quality Control Plan Research Articles

Conceptual Design of Quality Management Digitalization for FMCG Industry

Industry 4.0 era encourage FMCG manufacture industries in Indonesia to continuously innovating through digital technology adoption in their process, including quality management. Quality management digitalization in manufacture industry in Indonesia is now at the level of leaving paperwork documentation and analog communication in quality control; and have started to adopt computerized database and analysis. The absent of national software provider and academic study focusing on quality management digitalization concept has become an obstacle for Indonesia to evolve in Industry 4.0 era. This paper intended to provide conceptual design of integrated quality management digitalization to support FMCG industries in effective decision making and compliance to quality control plan; and to stimulate national software provide to develop digitalized quality management program

Questionnaire Survey of Japanese Medical Physicists on Working Conditions in 2020

The questionnaire survey was conducted in 2020 to investigate the working conditions of qualified medical physicists in Japan. We developed a web-based system for administering the questionnaire and surveyed 1,228 qualified medical physicists. The number of received responses was 405. We summarized the results of the survey by job category. The obtained results showed that most of the people working as certified medical physicists met the following conditions: (1) position of healthcare occupation, (2) direct supervisor is a medical doctor or a medical physicist, (3) licensed or passed an examination for a Class I Radiation Protection Supervisor, (4) without the license of professional radiotherapy technologist, (5) master's or doctor's degree, (6) being assigned to the section that is different from the radiological technologist section. The average annual salary was approximately 600,000 yen higher for those employed as medical physicists than for those employed as radiotherapy technologists. The percentage of work performed by a certified medical physicist in radiation therapy greatly varies depending on whether the physicist is dedicated to treatment planning and equipment quality control. Alternatively, the proportion of the true duties of medical physicists in charge of radiation therapy, as considered by qualified medical physicists in radiation therapy, was the same regardless of whether they were working full-time or not. The results of this survey updated the working status of certified medical physicists in Japan. We will continue to conduct the survey periodically and update the information to contribute to the improvement of the working conditions of medical physicists and policy recommendations.

Applications of artificial intelligence in radiophysics

Artificial intelligence (AI) is playing an important role in radiation oncology. One of the most important applications is in radiotherapy physics. In this field, it has improved the automation of radiotherapy plan design and quality control (QC), thereby promoting and ensuring individualized precision treatment. This article reviews the applications and research on AI in the physics of radiotherapy and projects the prospects of AI in the following aspects: radiotherapy plan design, radiotherapy quality assurance, and QC, organs at risk contouring, dose prediction, etc.

ORBIT-RT: A Real-Time, Open Platform for Knowledge-Based Quality Control of Radiotherapy Treatment Planning.

Access to knowledge-based treatment plan quality control has been hindered by the complexity of developing models and integration with different treatment planning systems (TPS). Online Real-time Benchmarking Information Technology for RadioTherapy (ORBIT-RT) provides a free, web-based platform for knowledge-based dose estimation that can be used by clinicians worldwide to benchmark the quality of their radiotherapy plans. The ORBIT-RT platform was developed to satisfy four primary design criteria: web-based access, TPS independence, Health Insurance Portability and Accountability Act compliance, and autonomous operation. ORBIT-RT uses a cloud-based server to automatically anonymize a user's Digital Imaging and Communications in Medicine for RadioTherapy (DICOM-RT) file before upload and processing of the case. From there, ORBIT-RT uses established knowledge-based dose-volume histogram (DVH) estimation methods to autonomously create DVH estimations for the uploaded DICOM-RT. ORBIT-RT performance was evaluated with an independent validation set of 45 volumetric modulated arc therapy prostate plans with two key metrics: (i) accuracy of the DVH estimations, as quantified by their error, DVHclinical - DVHprediction and (ii) time to process and display the DVH estimations on the ORBIT-RT platform. ORBIT-RT organ DVH predictions show < 1% bias and 3% error uncertainty at doses > 80% of prescription for the prostate validation set. The ORBIT-RT extensions require 3.0 seconds per organ to analyze. The DICOM upload, data transfer, and DVH output display extend the entire system workflow to 2.5-3 minutes. ORBIT-RT demonstrated fast and fully autonomous knowledge-based feedback on a web-based platform that takes only anonymized DICOM-RT as input. The ORBIT-RT system can be used for real-time quality control feedback that provides users with objective comparisons for final plan DVHs.

Analysis Of Quality Control Plans For Bridge Over The River Maza Jugla Accoring To COST TU 1406 Methodology

Bridges are one of the most expensive elements of the road network, and therefore in the bridge management process, it is very important to make the most technically efficient and cost-effective decisions about planned actions such as maintenance, rehabilitation and reconstruction works. Decisions have to be based both on the current situation and possible future options and alternatives.The European Cooperation in Science and Technology (COST) during the action TU 1406 “Quality specifications for roadway bridges, standardization at a European level (BridgeSpecs)” in the period from 2014 to 2019 has developed the framework for the development of bridge Quality Control Plans (QCP) including the system of data collection, data processing and outcomes.This article analyses and compares different Quality Control Plans developed according to COST TU 1406 methodology for the existing bridge over the river Maza Jugla, located on regional road P10 at km 34.80 in Latvia.

Study on Structural Reliability of Prestressed Reinforced Concrete Beam Bridges Based on Full Probability Analysis

A three dimensional(3D) finite element model is established for a prestressed concrete girder bridge, list the limit state equation and variable probability distribution model, obtain the failure probability and reliability index of the limit state equation based on the Monte-Carlo method, investigate the reliability index’s sensitivity to random variables for limit state equations of bridge bearing capacity. The specific method of the research on the structure reliability index calculation is to select a suitable way that can fit the research’s object among the center point method, the checking-point method, the Monte-Carlo method, the importance sampling method, and so on. Authors use finite element software ANSYS to build model and perform 3D force analysis. According to the results, authors can determine the bridges’ failure modes under the state of 3D stress. Then, authors can list the possible limit state equations related to Stiffness, strength, function, durability, and some character else. After determining the bridge’s structural limit state equation and the probability distribution model of the variables, determine the distribution function of each impact factor and its characteristic parameters through the site survey data and other related data surveys. Then, use the Monte-Carlo method for the calculation of bridge reliability index, obtain the failure probability and reliability index of each limit state equation, analyze the sensitivity of each variable to the reliability index under the ultimate state of the bridge’s bearing capacity. At last, authors give construction quality control plans and suggestions according to the data above.

Application of quality control plan to existing bridges

The long-term quality assurance of bridges demands an adequate quality control plan detailing the main required activities and assessment tools. This paper presents the application of a quality control plan on two existing reinforced concrete bridges located in Portugal and North Macedonia. Based on the available results from visual inspections and non-destructive tests, defects and corresponding damage processes were identified. The structural safety of the case studies was assessed by means of a reliability index considering the identified damages. The reliability index computation was supported by a nonlinear finite element analysis. The computed reliability index that reflects the actual (‘today’) bridge condition was used as the base information in the preparation of possible maintenance scenarios. Three different maintenance scenarios were considered, namely, the improvement (corrective scenario), reduction (do nothing and rebuilt scenario), or delay in the reduction (preventative scenario) of the performance of the structure. By comparison of normalised net present values of the key performance indicators (reliability, safety, availability and costs), the most appropriate scenarios are found.

DESAIN KONSEPTUAL DIGITALISASI MANAJEMEN MUTU PADA INDUSTRI FMCG

Industry 4.0 era encourage FMCG manufacture industries in Indonesia to continuously innovating through digital technology adoption in their process, including quality management. Quality management digitalization in manufacture industry in Indonesia is now at the level of leaving paperwork documentation and analog communication in quality control; and have started to adopt computerized database and analysis. The absent of national software provider and academic study focusing on quality management digitalization concept has become an obstacle for Indonesia to evolve in Industry 4.0 era. This paper intended to provide conceptual design of integrated quality management digitalization to support FMCG industries in effective decision making and compliance to quality control plan; and to stimulate national software provider to develop digitalized quality management program. The research use descriptive qualitative method through literature review of articles indexed in Garuda and Mendeley from 2017 to 2020 to make sure if there any previous research studied quality management digitalization for FMCG industry, and thus the review will be used as a strong reason to develop concept of quality management digitalization. The result showing no research found that exclusively studied about quality management digitalization for FMCG, and thus concept of quality management digitalization for FMCG is proposed as a baseline foundation for program developer to develop an integrated software in quality management digitalization for FMCG.

Spatiotemporal Variations and Uncertainty in Crop Residue Burning Emissions over North China Plain: Implication for Atmospheric CO2 Simulation

Large uncertainty exists in the estimations of greenhouse gases and aerosol emissions from crop residue burning, which could be a key source of uncertainty in quantifying the impact of agricultural fire on regional air quality. In this study, we investigated the crop residue burning emissions and their uncertainty in North China Plain (NCP) using three widely used methods, including statistical-based, burned area-based, and fire radiative power-based methods. The impacts of biomass burning emissions on atmospheric carbon dioxide (CO2) were also examined by using a global chemical transport model (GEOS-Chem) simulation. The crop residue burning emissions were found to be high in June and followed by October, which is the harvest times for the main crops in NCP. The estimates of CO2 emission from crop residue burning exhibits large interannual variation from 2003 to 2019, with rapid growth from 2003 to 2012 and a remarkable decrease from 2013 to 2019, indicating the effects of air quality control plans in recent years. Through Monte Carlo simulation, the uncertainty of each estimation was quantified, ranging from 20% to 70% for CO2 emissions at the regional level. Concerning spatial uncertainty, it was found that the crop residue burning emissions were highly uncertain in small agricultural fire areas with the maximum changes of up to 140%. While in the areas with large agricultural fire, i.e., southern parts of NCP, the coefficient of variation mostly ranged from 30% to 100% at the gridded level. The changes in biomass burning emissions may lead to a change of surface CO2 concentration during the harvest times in NCP by more than 1.0 ppmv. The results of this study highlighted the significance of quantifying the uncertainty of biomass burning emissions in a modeling study, as the variations of crop residue burning emissions could affect the emission-driven increases in CO2 and air pollutants during summertime pollution events by a substantial fraction in this region.

Air Pollution and Urban Green Space: Evidence of Environmental Injustice in Adama, Ethiopia

While air pollution data in Ethiopia is limited, existing studies indicate high levels of both ambient and household air pollution; rapid urbanization also threatens the preservation of urban green spaces. In this study, environmental injustice, or the disproportionate burden of environmental exposures on persons of lower socioeconomic status (SES), was explored among women in Ethiopia using a mother and child cohort from the city of Adama. Land-use regression models were previously developed for modeling ambient nitrogen dioxide (NO2) and nitrogen oxides (NOx) throughout Adama, while household air pollution (cooking fuel type) and the presence of green space were assessed through questionnaires and home visits, respectively. The odds of being exposed to these environmental factors were analyzed in association with two SES indicators, education and occupation, using logistic regression. Our results indicate the presence of environmental injustice in Adama, as women with lower SES shouldered a higher burden of air pollution exposure and enjoyed less urban green space than their higher SES counterparts. These findings encourage the prioritization of air quality control and urban planning resources toward policy action within lower SES areas. From a societal perspective, our results also support more upstream interventions, including investment in educational and occupational opportunities. Still, a human rights approach is emphasized, as governments are responsible for protecting the right to a clean environment, especially for those disproportionately exposed. To the best of our knowledge, this is the first study on environmental injustice in Ethiopia, and the first in Sub-Saharan Africa to investigate the inequalities of ambient and household air pollution exposure as well as urban green space access in the same cohort.

A brief introduction to the FUTang Updating medical REcords (FUTURE) database.

Futang Research Center of Pediatric Development (FRCPD), the first nonprofit social service organization engaging in pediatric research in China, was founded in May 2013. Until August 2021, FRCPD has 40 tertiary children’s hospitals, accounting for about 65.6% of all national public children’s hospitals, which was reported to be 61 in China Health Statistical Yearbook (2020). The hospitals are distributed in 30 provinces, autonomous regions, and municipalities (except for Tibet autonomous region), and most of them are in the capital of the province, forming a broad frontline representing the best quality of health care for the diagnosis and treatment of children’s disease in China. Based on the idea of sharing, FRCPD realized the exchange of experts, medical resources, research findings, educational events, preventive strategies, and management experiences among members. In the long run, FRCPD aims to continuously promote the quality of healthcare and medical service capability for children in China. The FUTang Updating medical REcords (FUTURE) database was born in 2019 in response to the initiative of “sharing of healthcare data resources” by the National Health Commission of the People’s Republic of China. In the meantime, the Children’s Health Data Science Committee was established by FRCPD and designated to be in charge of the FUTURE database. The core objective of FUTURE is to promote data utilization and realize mutual development of member hospitals by strengthening the cooperation and sharing of healthcare data. Given that FUTURE is a valuable research tool, we aim to present the essential aspects of the database including the data source, quality control process, and collected variables in this article. A total of 26 hospitals in FRCPD have come to an agreement and uploaded the first-page information of inpatient medical records to the FUTURE database annually. All the 26 hospitals are tertiary hospitals, of which 21 are located in the capital of the province, meaning the most representative sample of hospitalized children in that area. The name of the included hospitals is listed in Table S1. The data uploading docking and format standards are referred to the requirements made by the Hospital Quality Monitoring System (HQMS) for the collection of first-page information of inpatient medical records in the performance appraisal and medical quality management of national tertiary public hospitals (2019). The quality control plan of the FUTURE database mainly consists of three parts: de-identification, coding instruction, and data cleaning. For de-identification, information that can be used to identify the patients or their parents was masked or deleted. Coding for diagnosis, histology, and operation was using International Classification of Diseases (10th Revision), International Classification of Diseases for Oncology (3rd Edition), and International Classification of Diseases 9th Revision Clinical Modification Operations and Procedures 3rd edition (ICD-9-CM-3), respectively, as unified standards. After code standardization, data cleaning was conducted to ensure the uniqueness, integrity, and validation of each record.1 The overview of the quality control process is shown in Figure 1. The collected variables include identification variables, basic information including sociodemographic and geographic variables, admission and discharge information, clinical factors related to diagnosis and operational treatment, and hospitalization expenses. The detailed list of collected variables is shown in Table 1. After quality control and data cleaning, the continuously updating database now has more than 6 million medical records from the year 2016 to 2020. The huge sample covers all the ICD-10 items that are related to children’s illnesses. In the years to come, the FUTURE will be updated annually with the medical records in the former year. The database is now accessible upon an application within the FRCPD group and anyone in the FRCPD member institution can apply for research purposes. Up till now, several studies about the epidemiology of childhood diseases or management optimization have been published based on the database.2, 3 As time goes on, with more hospitals being involved and the data volume getting bigger, the database would provide more possibilities in research and play an important role in making scientific decisions on children’s health care. None. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Sorrentina Peninsula: Geographical Distribution of the Indoor Radon Concentrations in Dwellings—Gini Index Application

The radon isotope (222Rn, half-life 3.8 days) is a radioactive byproduct of the 238U decay chain. Because radon is the second biggest cause of lung cancer after smoking, dense maps of indoor radon concentration are required to implement effective locally based risk reduction strategies. In this regard, we present an innovative method for the construction of interpolated maps (kriging) based on the Gini index computation to characterize the distribution of Rn concentration. The Gini coefficient variogram has been shown to be an effective predictor of radon concentration inhomogeneity. It allows for a better constraint of the critical distance below which the radon geological source can be considered uniform, at least for the investigated length scales of variability; it also better distinguishes fluctuations due to environmental predisposing factors from those due to random spatially uncorrelated noise. This method has been shown to be effective in finding larger-scale geographical connections that can subsequently be connected to geological characteristics. It was tested using real dataset derived from indoor radon measurements conducted in the Sorrentina Peninsula in Campania, Italy. The measurement was carried out in different residences using passive detectors (CR-39) for two consecutive semesters, beginning in September–November 2019 and ending in September–November 2020, to estimate the yearly mean radon concentration. The measurements and analysis were conducted in accordance with the quality control plan. Radon concentrations ranged from 25 to 722 Bq/m3 before being normalized to ground level, and from 23 to 933 Bq/m3 after being normalized, with a geometric mean of 120 Bq/m3 and a geometric standard deviation of 1.35 before data normalization, and 139 Bq/m3 and a geometric standard deviation of 1.36 after data normalization. Approximately 13% of the tests conducted exceeded the 300 Bq/m3 reference level set by Italian Legislative Decree 101/2020. The data show that the municipalities under investigation had no influence on indoor radon levels. The geology of the monitored location is interesting, and because soil is the primary source of Rn, risk assessment and mitigation for radon exposure cannot be undertaken without first analyzing the local geology. This research examines the spatial link among radon readings using the mapping based on the Gini method (kriging).

UAV-BASED PHOTOGRAMMETRY DATA TRANSFORMATION AS A BUILDING INSPECTION TOOL: APPLICABILITY IN MID-HIGH-RISE BUILDING

The photogrammetric concept is used as a practical implementation of this study. Data management is proposed as an active contribution in the process of data integration and data in-operability to develop solutions based on UAV-based Photogrammetry as part of building inspection activities. Point Cloud adjusts the main role as data to initialize objects whose information can be represented in 2D / 3D / 4D rich-data format. Decision making on each management framework is planned with the DJI Go and Pix4D Capture Application which is controlled by a smartphone that has been pre-configured for the plan UAV flights. The flight plan quality control, flight mission supervision, and data acquisition results are important factors in the management and related infor-mation framework. The Point Cloud created by the SfM (Structure from Motion) application is then imported by Autodesk Recap and reconstructed in Revit BIM. The 3D Point Cloud is lastly enhanced with some practically detailed information to contribute to the data management experiment. The collaboration model of this study is presented using AR / VR (Augmented Reality / Virtual Reality) to enable mobile monitoring as a research objective and substantial examination. The essence of this study is to develop UAV-based Photogrammetry / BIM / AR-VR as a method to reduce the risk of data mismatches, monitor communications, and increase the impact of practical instructions on de-cision making on building inspection activities. The results of each verified workflow show that the methodology applied produces informational and visual data products that allow user mobility within the scope of building inspection and monitoring. Furthermore, device limitations do not affect the data acquisition process to provide user safety and efficiency.

Supply chain resilience and industry 4.0: a evaluation of the Brazilian northeast automotive OEM scenario post COVID-19

COVID-19 outbreak has heavily impacted the manufacturing industry, including Brazilian Automotive Industry. The effects of COVID-19 created restrictions in several industry processes as supply chain. On the other hand, several industry 4.0 technologies is able to support the industry supply chain activities in the COVID 19 scenarios, as well it may contributed for the automotive industry recovery and it will define the next steps of this industry. A supply chain is a network between a company and its suppliers to produce and distribute a specific product to the final buyer. Industry 4.0 is related to the technology development and the digitalization process that improve significantly productivity. Considering the automotive process, an important reference model is described in Advanced Product Quality Planning and Control Plan, that is a manual that communicate the guidelines of the product quality planning and control plan for internal and external suppliers. In this scenario, this paper evaluated the current situation and the future outlook for the adoption of Industry 4.0 technologies in the automotive OEM post-pandemic scenario on the point of view of automotive specialists. The results of this research provide an overview of the current situation and the future outlook for the usage of Industry 4.0 technologies by the Brazilian Northeast automotive OEM, from the perspective of manufacturing engineering experts on APQP.

Quality Control on Minimizing Defect Product on 20 OE Yarn

Industrial businesses in Indonesia realize that consumer desires have changed over time. Consumers desire that becomes the main priority is quality. PT. Bitrate Industries, as a company that produces yarn in Semarang, always strives to improve product quality to the desires of consumers. The company faces quality control problems: the production process of 20 OE yarn, producing the highest defective products. The Six Sigma approach analyzes the causes of defects, identifies sources of variation, proposes improvements with 5W + 1H, and implements a quality control plan. Most defects occur in the production process in the autocross engine, which is caused by engine wear. Implementation of the kaizen approach can be given proposals in the form of improvements in maintenance, according to the existing scheduling and periodic replacement of parts. This study concludes that the proportion of defects is still in the controlled stage, but the quality control of the product is still needed. A quality improvement project with a Six Sigma approach can benefit any company that needs to find the most efficient way to improve product quality.

Design and analysis of automated external defibrillator (AED) using new service development

Coronary heart disease has become the major health issue that causes sudden heart attacks. In Indonesia, the number of death due to heart attack has been increased significantly. The purpose of this study is to design a new service development for Automated External Defibrillator Services in the public. The method used is conjoint analysis, cluster analysis, quality function deployment, process flow diagram and quality control plan. The results provided include user preferences regarding AED services, AED user segmentation, designing technical responses, designing operational procedures and designing quality control plans. In aggregate, users choose the website as a platform to guide the direction to the AED location and AED socialization, AED placement in or near the medical room and emergency telephone is equipment that must be placed with AED.

Cold storage-mediated rearing of Trichogramma evanescens Westwood on eggs of Plodia interpunctella (Hübner) and Galleria mellonella L.

The egg parasitoid Trichogramma evanescens Westwood is considered as an efficient biological control agent for managing several lepidopteran pests and it is widely distributed throughout the world. Mass rearing protocols of parasitoids that are currently in use in biocontrol programs require a meticulous quality control plan, in order to optimize their efficacy, but also their progeny production capacity. In this paper, the effect of different factors on the quality control in mass rearing of T. evenescens, using Plodia interpunctella (Hübner) and Galleria mellonella L. as host species, were investigated. The impact of egg agewas significant in the rates of parasitism, for both host species tested. Significantly highest percent of parasitoid emergence was noticed in two day-old eggs for both host species, while one day-old eggs day exhibited the maximum emergence when both species were used togetherin the same trials. Age-dependent storage egg preservation at either 4 or 9°C significantly influenced the parasitism percentages on both species. The highest parasitism percentage was recorded in two day-old G. mellonella eggs that are kept for 15 days at 9°C while the lower in one day-old P. interpunctella eggs for 60 d storage. Moreover, the highest parasitoid mortality was recorded in T. evanescens reared either on P. interpunctella or G. mellonella at 20°C. Rearing of the parasitoid on a mixture of eggs of both host species resulted in higher parasitism, but not always in higher rates of parasitoid emergence. The results of the present work provide useful information that can be further utilized in rearing protocols of T. evanescens.

Study Risk Minimization of The Use Bottled Drinking Water (BDW) By Consumers Using Hazard Analysis Critical Control Point (HACCP) Method

Bottled drinking water (BDW) is an effort to meet the demand for drinking water needs of the community which continues to increase every year. BDW is the community’s main choice because it can be consumed directly without the need to cook it first. The high demand for drinking water produced by bottled water requires a comprehensive, easy to apply, and standardized quality control method to maintain and improve the quality of the products produced so that they are safe for consumption by bottled drinking water customers. The suitable method for quality control is the method Hazard Analysis Critical Control Point (HACCP). This method is a risk analysis system by establishing an appropriate control and supervision system to avoid irregularities that can lead to poor quality of drinking water products produced, as well as producing quality bottled water products. The HACCP method can be applied to all aspects of production and aspects of human resources (HR) in bottled water starting from raw water management until the product is produced. In this method, there are 5 important principles used, such as analyzing the risk of hazards that can occur during the production process, determining the critical point of hazard risk analysis, determining critical limits, preparing monitoring system monitoring procedures, and finally preparing corrective actions to avoid deviations from critical limits. Based on the analysis of existing conditions at the BDW in Cirebon City, there are advantages and disadvantages on its own in the production process. For example, the poor performance of some treatment units and the need for control can be caused by replacing treatment units that exceed usage limits and irregular replacement schedules that can affect the water quality of these products. The HACCP method is needed in planning quality control to evaluate the performance of the BDW production processing unit, and determine the quality control of bottled drinking water products to minimize negative impacts for customers who consume them.

Prediction of Dimensional Changes of Low-Cost Metal Material Extrusion Fabricated Parts Using Machine Learning Techniques

Additive manufacturing (AM) is a layer-by-layer manufacturing process. However, its broad adoption is still hindered by limited material options, different fabrication defects, and inconsistent part quality. Material extrusion (ME) is one of the most widely used AM technologies, and, hence, is adopted in this research. Low-cost metal ME is a new AM technology used to fabricate metal composite parts using sintered metal infused filament material. Since the involved materials and process are relatively new, there is a need to investigate the dimensional accuracy of ME fabricated metal parts for real-world applications. Each step of the manufacturing process, from the material extrusion to sintering, might significantly affect the dimensional accuracy. This research provides a comprehensive analysis of dimensional changes of metal samples fabricated by the ME and sintering process, using statistical and machine learning algorithms. Machine learning (ML) methods can be used to assist researchers in sophisticated pre-manufacturing planning and product quality assessment and control. This study compares linear regression to neural networks in assessing and predicting the dimensional changes of ME-made components after 3D printing and sintering process. In this research, the ML algorithms present a significantly high coefficient of determination (i.e., 0.999) and a very low mean square error (i.e., 0.0000878). The prediction outcomes using a neural network approach have the smallest mean square error among all ML algorithms and it has quite small p-values. So, in this research, the neural network algorithm has the highest accuracy. The findings of this study can help researchers and engineers to predict the dimensional variations and optimize the printing and sintering process parameters to obtain high quality metal parts fabricated by the low-cost ME process.

An application of probability density function for the analysis of PM2.5 concentration during the COVID-19 lockdown period

The first Covid-19 patient in India was reported on January 30, 2020 at the state of Kerala. The patient number rose to three by February 3, 2020. In the month of March 2020, the transmissions started to increase when the people started to return back to India from the Covid-19 affected countries. On March 12, a 76-year-old man having a travel history to Saudi Arabia was the first reported fatality in India due to Covid 19. Then for the prevention of the propagation of Covid, the Indian government declared a state of health emergency and strict counter measures were taken, including locking down of cities, prohibiting almost all avoidable activities and restricting population's mobility. From March 24, 2020 due to the complete lockdown in the country, human activities were heavily restricted in the whole geographical regions of India. This pandemic lockdown eventually serves as an opportunity to observe the background concentrations of pollutants in the atmosphere. The PM 2.5 distribution can affect human health and to overcome this problem, setting up of regulation for PM is necessary. In the present study Probability density functions (PDF) method have been utilised for the investigation of PM 2.5 pollutant data distribution of five countries namely, India, China, France, Brazil and United States of America (USA) for their respective lockdown period of 2020 and corresponding same period of 2019. A detailed study has been done for India, and for that purpose India has been divided into three regions (Central India, Coastal India and Indo-Gangetic Plain (IGP)) on the basis of different meteorological conditions. PM 2.5 concentration for hourly basis has been analysed for the lockdown period 24th March to 15th June 2020 and compared with the PM 2.5 concentration of previous year 2019 for the same time period. To understand the effect of lockdown in PM 2.5 emission in India, which will give us an idea about the background concentration, PDFs (probability density functions) have also been generated for the whole year from 2015 to 2019. The “goodness-of-fit” of the probability density functions, to the data, was assessed, using various statistical indices (Chi-square test). Results show that the PM 2.5 reduction during the lockdown period of 2020 as compared to the same period of 2019 is sufficiently large. This study will give a certain degree of idea to the regulatory bodies on planning and implementation of strict air quality control plans.