Benefits Of Quality Assurance Research Articles

Benefits of Quality Assurance and Control in Construction Industry

Quality assurance and control has been established by researchers to provide guidance for establishing an appropriate quality management procedure, in order to lower cost, increase productivity and customer's satisfaction, as well as market share in construction. This can assist construction industry to achieve successfully, their objectives, and ensure that all phases of construction projects consistently meet client's requirements. Basically, the objective of the study is to assess the level of quality assurance and control in construction through compliance evaluation and assessing the benefits and factors of implementing quality assurance and control on construction projects in Abuja and Environs. The research methodology adopted was an in-depth literature review and questionnaire administration while the data collected were subjected to descriptive statistical analysis through the application of percentage, frequency, mean and score. The findings have shown that construction firm’s adherence and compliance to International Standard Organisation series is low. The benefits of adopting Quality assurance and control are to improve site management, enhance reputation for good design and proper effective planning. It also highlighted factors affecting quality assurance and control implementation to be incompatible tendering procedure, design complexity, poor performance of quality and low tendency for team work. Finally, the measures for improving quality standard are enforcement of quality standard by agency of government and regulatory bodies and provision of training service on quality assurance. The study also recommends that all stakeholders need to understand the importance of quality assurance and control standards and also inculcate them throughout the design productive phase of their projects.

Quality assured implementation of the Slovenian breast cancer screening programme.

The organised, population-based breast cancer screening programme in Slovenia began providing biennial mammography screening for women aged 50-69 in 2008. The programme has taken a comprehensive approach to quality assurance as recommended by the European guidelines for quality assurance in breast cancer screening and diagnosis (4th edition), including centralized assessment, training and supervision, and proactive monitoring of performance indicators. This report describes the progress of implementation and rollout from 2003 through 2019. The screening protocol and key quality assurance procedures initiated during the planning from 2003 and rollout from 2008 of the screening programme, including training of the professional staff, are described. The organisational structure, gradual geographical rollout, and coverage by invitation and examination are presented. The nationwide programme was up and running in all screening regions by the end of 2017, at which time the nationwide coverage by invitation and examination had reached 70% and 50%, respectively. Nationwide rollout of the population-based programme was complete by the end of 2019. By this time, coverage by invitation and examination had reached 98% and 76%, respectively. The participation rates consistently exceeded 70% from 2014 to 2019. The successful implementation of the screening programme can be attributed to an independent central management, external guidance, and strict adherence to quality assurance procedures, all of which contributed to increasing governmental and popular support. The benefits of quality assurance have influenced all aspects of breast care and have provided a successful model for multidisciplinary management of other diseases.

Conceptual model for pair design and pair testing based on the characteristics of pair programming

Pair programming is a method that is widespread in the field of agile software development (ASD) and is acknowledged as state of the art of programming. This article initially addresses the question of what constitutes the key attributes of pair programming. Therefore, we analysed the extent to which these attributes can be applied to the development-related areas of human-centred design (HCD) and the quality assurance (QA) of software. The results of this analyses lead to the presentation and consideration of a new conceptual model for the application of the attributes of pair programming in the context of pair design (HCD) and/or pair testing (QA). The discussion shows that a transferability and application is appropriate and that both HCD and QA benefit, particularly in terms of the product quality and product throughput time.

SNOMED CT Implementation

Clinical practice as well as research and quality-assurance benefit from unambiguous clinical information resulting from the use of a common terminology like the Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). A common terminology is a necessity to enable consistent reuse of data, and supporting semantic interoperability. Managing use of terminology for large cross specialty Electronic Health Record systems (EHR systems) or just beyond the level of single EHR systems requires that mappings are kept consistent. The objective of this study is to provide a clear methodology for SNOMED CT mapping to enhance applicability of SNOMED CT despite incompleteness and redundancy. Such mapping guidelines are presented based on an in depth analysis of 14 different EHR templates retrieved from five Danish and Swedish EHR systems. Each mapping is assessed against defined quality criteria and mapping guidelines are specified. Future work will include guideline validation.

Quality science and quality assurance: observations of an environmental scientist.

The purpose of this manuscript is to examine the relationship between quality science (QS) and quality assurance (QA). Many research scientists definitely want to do QS, but are afraid or do not want to do QA because they are intimidated by the QA process or they do not appreciate the benefits of QA. Therefore, the relationship between QS and QA is examined in this manuscript by an environmental scientist who has conducted 30 years of research in university, contract and government laboratories. To start, QS is defined in this paper as data that are published in the peer-reviewed literature. The quality of the research data is assumed by the general scientific population to be directly proportional to the status of the journal. For example, it is highly prestigious to have an article published in Science. At the U.S. EPA, the procedure for sending a manuscript to a journal for publication is the responsibility of the senior author. The senior author of an EPA-sponsored manuscript is expected to have the manuscript reviewed by the coauthors (they should also review the data), then the manuscript must be reviewed by at least two other scientists, one of whom must be from outside the authors' division. After this review and approval by management, the manuscript is sent to a peer-reviewed journal, where it is reviewed by several anonymous scientists as determined by the journal. After the comments of the reviewers are addressed, the manuscript can either be accepted or rejected for publication by the journal. For the purpose of this manuscript, the definition of QA is defined as the guarantee from a review team that the entire study was adequately and correctly conducted and recorded according to the study protocol. Many scientists view QS and QA as separate entities. From the scientist's perspective, QA procedures are not applicable to research studies, and should be used only for studies that will be submitted to either the EPA or the FDA for regulatory approval (i.e., Good Laboratory Practice [GLP] studies). However, QA can be applied to both types of studies. A QA review will examine all aspects of the study including data files (notebooks, protocols), as well as equipment, sample storage, actual experimental organisms (animals or cells) and the management of all study records. The data from a QA-reviewed study are therefore more defensible in a court of law, and more reproducible due to more through, chronological records. Generally speaking, few coauthors of a scientific manuscript analyze the raw data in the laboratory notebooks or inspect the laboratory equipment. Furthermore, coauthors generally have not been in the laboratory where the research was conducted in order to observe quality control measures. These are the areas where a QA review is extremely beneficial. In summary, data in the peer-reviewed literature do not undergo the same type of review as do data that have undergone a QA review. QA reviews assist EPA scientists in conducting and improving their research studies by identifying both excellent study practices and study deficiencies to be addressed, which thereby produces higher quality scientific data. In the opinion of this EPA Scientist and QA Manager, although QA reviews do require effort from the scientist, data from research studies are strengthened by QA review when compared to data from peer-reviewed studies that have not undergone a QA review. QA reviews should be viewed as part of the entire research process--a part that improves the overall quality of the data.

Good quality at low cost: Trends in quality assurance

AbstractFor as long as electronic devices have been produced the relationship between the costs and benefits of quality assurance has been discussed. At present this relationship is influenced by the increase in the complexity of integrated circuits and by the growing extent of automation in production. In this paper a way is presented showing how the cost of quality assurance can be decreased without loss of quality. Six steps to achieving this goal are described.

Quality assurance of geosynthetic lining systems

Why would the owner of a proposed geomembrane-lined facility agree to a cost increase of 20–40% to pay for quality assurance? Many owners now agree that the benefits of quality assurance are more than worth the extra cost. This paper describes quality assurance related to the design, manufacture, fabrication, installation and use of geosynthetic lining systems. Such lining systems are comprised of geomembranes and other geosynthetics such as geotextiles, geonets and geogrids. The need for third party quality assurance is stressed, i.e. quality assurance should be performed by a party other than the facility owner, the designer, or the geosynthetic manufacturer/installer. A special discussion is devoted to the quality assurance of the design, wherein design review by an independent organization is suggested and examples from actual installations show design mistakes which could have been identified if quality assurance had been provided. This paper is based on experience gained while conducting the quality assurance of a variety of installations as well as forensic investigations at many problem sites.