A framework for big data driven process analysis and optimization for additive manufacturing

2019 ◽  
Vol 25 (2) ◽  
pp. 308-321 ◽  
Author(s):  
Arfan Majeed ◽  
Jingxiang Lv ◽  
Tao Peng
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Additive Manufacturing ◽  
Production Efficiency ◽  
Process Analysis ◽  
Three Dimensional ◽  
Big Data Analytics ◽  
Production Performance ◽  
Content Type ◽  
Processing And Storage

Purpose This paper aims to present an overall framework of big data-based analytics to optimize the production performance of additive manufacturing (AM) process. Design/methodology/approach Four components, namely, big data application, big data sensing and acquisition, big data processing and storage, model establishing, data mining and process optimization were presented to comprise the framework. Key technologies including the big data acquisition and integration, big data mining and knowledge sharing mechanism were developed for the big data analytics for AM. Findings The presented framework was demonstrated by an application scenario from a company of three-dimensional printing solutions. The results show that the proposed framework benefited customers, manufacturers, environment and even all aspects of manufacturing phase. Research limitations/implications This study only proposed a framework, and did not include the realization of the algorithm for data analysis, such as association, classification and clustering. Practical implications The proposed framework can be used to optimize the quality, energy consumption and production efficiency of the AM process. Originality/value This paper introduces the concept of big data in the field of AM. The proposed framework can be used to make better decisions based on the big data during manufacturing process.

scholarly journals Anomaly data management and big data analytics: an application on disability datasets

2018 ◽  
Vol 2 (2) ◽  
pp. 164-176
Author(s):  
Zhiwen Pan ◽  
Wen Ji ◽  
Yiqiang Chen ◽  
Lianjun Dai ◽  
Jun Zhang
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Management ◽  
Big Data Analytics ◽  
Quality Data ◽  
Content Type ◽  
Data Mining Algorithms ◽  
Management Scheme ◽  
The Disabled ◽  
Mining Scheme

Purpose The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of the inherent characteristics of the disabled populations, so that working plans and policies, which can effectively help the disabled populations, can be made accordingly. Design/methodology/approach In this paper, the authors proposed a big data management and analytic approach for disability datasets. Findings By using a set of data mining algorithms, the proposed approach can provide the following services. The data management scheme in the approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. The data mining scheme in the approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments based on real-world dataset are conducted at the end to prove the effectiveness of the approach. Originality/value The proposed approach can enable data-driven decision-making for professionals who work with disabled populations.

Big data analytics – enabled cyber-physical system: model and applications

2019 ◽  
Vol 119 (5) ◽  
pp. 1072-1088
Author(s):  
Shuai Luo ◽  
Hongwei Liu ◽  
Ershi Qi
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Collection ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cyber Physical System ◽  
Content Type ◽  
Aero Engine ◽  
Communication Layer ◽  
Smart Data

Purpose The purpose of this paper is to propose a comprehensive framework for integrating big data analytics (BDA) into cyber-physical system (CPS) solutions. This framework provides a wide range of functions, including data collection, smart data preprocessing, smart data mining and smart data visualization. Design/methodology/approach The architecture of CPS was designed with cyber layer, physical layer and communication layer from the perspective of big data processing. The BDA model was integrated into a CPS that enables managers to make sound decisions. Findings The effectiveness of the proposed BDA model has been demonstrated by two practical cases − the prediction of energy output of the power grid and the estimate of the remaining useful life of the aero-engine. The method can be used to control the power supply system and help engineers to maintain or replace the aero-engine to maintain the safety of the aircraft. Originality/value The communication layer, which connects the cyber layer and physical layer, was designed in CPS. From the communication layer, the redundant raw data can be converted into smart data. All the necessary functions of data collection, data preprocessing, data storage, data mining and data visualization can be effectively integrated into the BDA model for CPS applications. These findings show that the proposed BDA model in CPS can be used in different environments and applications.

Fraudulent financial reporting and data analytics: an explanatory study from Ireland

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ahmed Aboud ◽  
Barry Robinson
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Financial Reporting ◽  
Data Analytics ◽  
Traditional Approach ◽  
Big Data Analytics ◽  
Fraudulent Financial Reporting ◽  
Fraud Prevention ◽  
Content Type ◽  
Detection Techniques

Purpose This paper aims to explore the effectiveness of fraud prevention and detection techniques, including data analytics, machine learning and data mining, and to understand how widespread the use of data analytics is across different sectors and to identify and understand the potential barriers to implementing these techniques to detect and prevent fraud. Design/methodology/approach A survey was administered to 73 Irish businesses to determine to what extent traditional approach, data mining or text mining are being used to prevent or detect fraudulent financial reporting, and to determine the perception level of their effectiveness. Findings The study suggests that whilst data analytics is widely used by businesses in Ireland there is an under-utilisation of data analytics as an effective tool in the fight against fraud. The study suggests there are barriers that may be preventing companies from implementing advanced data analytics to detect financial statement fraud and identifies how those barriers may be overcome. Originality/value In contrast to the majority of literature on big data analytics and auditing, which lacks empirical insight into the diffusion, effectiveness and obstacles of data analytics, this explanatory study contributes by providing useful insights from the field on big data analytics. While the extant auditing literature generally addresses the avenues of big data utilisation in auditing domain, our study explores particularly the use big data analytics as a fraud prevention and detection techniques.

Trends and Opportunities in Health Analytics as a Service and Implications for Use in Low Resource Settings: A Literature Review Abstract (Preprint)

2019 ◽  
Author(s):  
Meghana Bastwadkar ◽  
Carolyn McGregor ◽  
S Balaji
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Intensive Care ◽  
Literature Review ◽  
Health Monitoring ◽  
Data Analytics ◽  
Neonatal Intensive Care ◽  
Big Data Analytics ◽  
Healthcare Facilities

BACKGROUND This paper presents a systematic literature review of existing remote health monitoring systems with special reference to neonatal intensive care (NICU). Articles on NICU clinical decision support systems (CDSSs) which used cloud computing and big data analytics were surveyed. OBJECTIVE The aim of this study is to review technologies used to provide NICU CDSS. The literature review highlights the gaps within frameworks providing HAaaS paradigm for big data analytics METHODS Literature searches were performed in Google Scholar, IEEE Digital Library, JMIR Medical Informatics, JMIR Human Factors and JMIR mHealth and only English articles published on and after 2015 were included. The overall search strategy was to retrieve articles that included terms that were related to “health analytics” and “as a service” or “internet of things” / ”IoT” and “neonatal intensive care unit” / ”NICU”. Title and abstracts were reviewed to assess relevance. RESULTS In total, 17 full papers met all criteria and were selected for full review. Results showed that in most cases bedside medical devices like pulse oximeters have been used as the sensor device. Results revealed a great diversity in data acquisition techniques used however in most cases the same physiological data (heart rate, respiratory rate, blood pressure, blood oxygen saturation) was acquired. Results obtained have shown that in most cases data analytics involved data mining classification techniques, fuzzy logic-NICU decision support systems (DSS) etc where as big data analytics involving Artemis cloud data analysis have used CRISP-TDM and STDM temporal data mining technique to support clinical research studies. In most scenarios both real-time and retrospective analytics have been performed. Results reveal that most of the research study has been performed within small and medium sized urban hospitals so there is wide scope for research within rural and remote hospitals with NICU set ups. Results have shown creating a HAaaS approach where data acquisition and data analytics are not tightly coupled remains an open research area. Reviewed articles have described architecture and base technologies for neonatal health monitoring with an IoT approach. CONCLUSIONS The current work supports implementation of the expanded Artemis cloud as a commercial offering to healthcare facilities in Canada and worldwide to provide cloud computing services to critical care. However, no work till date has been completed for low resource setting environment within healthcare facilities in India which results in scope for research. It is observed that all the big data analytics frameworks which have been reviewed in this study have tight coupling of components within the framework, so there is a need for a framework with functional decoupling of components.

Dave Snowden on KM and big data/analytics: interview with David J. Pauleen

2017 ◽  
Vol 21 (1) ◽  
pp. 12-17 ◽  
Author(s):  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Theory And Practice ◽  
Content Type ◽  
Face To Face ◽  
The Relationship ◽  
A Company ◽  
Practical Implications ◽  
Scientific Officer

Purpose Dave Snowden has been an important voice in knowledge management over the years. As the founder and chief scientific officer of Cognitive Edge, a company focused on the development of the theory and practice of social complexity, he offers informative views on the relationship between big data/analytics and KM. Design/methodology/approach A face-to-face interview was held with Dave Snowden in May 2015 in Auckland, New Zealand. Findings According to Snowden, analytics in the form of algorithms are imperfect and can only to a small extent capture the reasoning and analytical capabilities of people. For this reason, while big data/analytics can be useful, they are limited and must be used in conjunction with human knowledge and reasoning. Practical implications Snowden offers his views on big data/analytics and how they can be used effectively in real world situations in combination with human reasoning and input, for example in fields from resource management to individual health care. Originality/value Snowden is an innovative thinker. He combines knowledge and experience from many fields and offers original views and understanding of big data/analytics, knowledge and management.

Effect of 3D printer enabled surface morphology and composition on coral growth in artificial reefs

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ilse Valenzuela Matus ◽  
Jorge Lino Alves ◽  
Joaquim Góis ◽  
Augusto Barata da Rocha ◽  
Rui Neto ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Chemical Composition ◽  
Chemical Elements ◽  
Three Dimensional ◽  
Coral Growth ◽  
Coralline Algae ◽  
Textured Surface ◽  
Crustose Coralline Algae ◽  
Statistical Parameters ◽  
Content Type

Purpose The purpose of this paper is to prove and qualify the influence of textured surface substrates morphology and chemical composition on the growth and propagation of transplanted corals. Use additive manufacturing and silicone moulds for converting three-dimensional samples into limestone mortar with white Portland cement substrates for coral growth. Design/methodology/approach Tiles samples were designed and printed with different geometries and textures inspired by nature marine environment. Commercial coral frag tiles were analysed through scanning electron microscopy (SEM) to identify the main chemical elements. Raw materials and coral species were selected. New base substrates were manufactured and deployed into a closed-circuit aquarium to monitor the coral weekly evolution process and analyse the results obtained. Findings Experimental results provided positive statistical parameters for future implementation tests, concluding that the intensity of textured surface, interfered favourably in the coralline algae biofilm growth. The chemical composition and design of the substrates were determinant factors for successful coral propagation. Recesses and cavities mimic the natural rocks aspect and promoted the presence and interaction of other species that favour the richness of the ecosystem. Originality/value Additive manufacturing provided an innovative method of production for ecology restoration areas, allowing rapid prototyping of substrates with high complexity morphologies, a critical and fundamental attribute to guarantee coral growth and Crustose Coralline Algae. The result of this study showed the feasibility of this approach using three-dimensional printing technologies.

Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajesh Kumar Singh ◽  
Saurabh Agrawal ◽  
Abhishek Sahu ◽  
Yigit Kazancoglu
Keyword(s):  
Health Care ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Sector ◽  
Future Research ◽  
Research Gaps ◽  
Content Type

PurposeThe proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.Design/methodology/approachFora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.FindingsBD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.Research limitations/implicationsThe proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.Originality/valueThere are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.

The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: a dynamic capability view

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamad Bahrami ◽  
Sajjad Shokouhyar
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Firm Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Culture

PurposeBig data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.Design/methodology/approachThe study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.FindingsThe results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.Originality/valueThe present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

Animal orthosis fabrication with additive manufacturing – a case study of custom orthosis for chicken

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wiktoria Maria Wojnarowska ◽  
Jakub Najowicz ◽  
Tomasz Piecuch ◽  
Michał Sochacki ◽  
Dawid Pijanka ◽  
...  
Keyword(s):  
Veterinary Medicine ◽  
Additive Manufacturing ◽  
Computer Aided Design ◽  
Three Dimensional ◽  
Fused Deposition Modelling ◽  
Content Type ◽  
Fused Deposition ◽  
Secondary Objective ◽  
Traditional Manufacturing ◽  
Aided Design

Purpose Chicken orthoses that cover the ankle joint area are not commercially available. Therefore, the main purpose of this study is to fabricate a customised temporary Ankle–Foot Orthosis (AFO) for a chicken with a twisted ankle using computer-aided design (CAD) and three-dimensional (3D) printing. The secondary objective of the paper is to present the specific application of Additive Manufacturing (AM) in veterinary medicine. Design/methodology/approach The design process was based on multiple sketches, photos and measurements that were provided by the owner of the animal. The 3D model of the orthosis was made with Autodesk Fusion 360, while the prototype was fabricated using fused deposition modelling (FDM). Evaluation of the AFO was performed using the finite element method. Findings The work resulted in a functional 3D printed AFO for chicken. It was found that the orthosis made with AM provides satisfactory stiffen and a good fit. It was concluded that AM is suitable for custom bird AFO fabrication and, in some respects, is superior to traditional manufacturing methods. It was also concluded that the presented procedure can be applied in other veterinary cases and to other animal species and other parts of their body. AM provides veterinary with a powerful tool for the production of well-fitted and durable orthoses for animals. Research limitations/implications The study does not include the chicken's opinion on the comfort or fit of the manufactured AFO due to communication issues. Evaluation of the final prototype was done by the researchers and the animal owner. Originality/value No evidence was found in the literature on the use of AM for chicken orthosis, so this study is the first to describe such an application of AM. In addition, the study demonstrates the value of AM in veterinary medicine, especially in the production of devices such as orthoses.

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