Industrial Paradigm Research Articles

Real-time monitoring solution with vibration analysis for industry 4.0 ventilation systems

Predictive maintenance has revealed as one of the paradigms of Industry 4.0. This paper addresses a complete system for the acquisition, computing, monitoring and communication of ventilation equipment in underground tunnels based on TCP/IP protocol and accessible via WEB services. Not only does the proposed system collect different sensor data (temperatures, vibrations, pressures, tilt angles or rotational speed), it performs local data processing as well. This feature is the newest and most important of all those provided by the system design, and there is no equipment that offers a similar performance in current ventilation systems. This paper shows the design and implementation of the equipment (system architecture and processing), as well as the experimental results obtained.

Introduction: Uncomics

The artists featured in this issue all appeared in C’est Bon Anthology (CBA) #56&57: Uncomics, published by C’est Bon Kultur (CBK), in 2022. CBK’s stated purpose is to support, evolve and disseminate comics with higher artistic ambitions – that is, comics made away from the commercial factory paradigm of the mainstream industry. ‘Un/comics’ was edited by comics artist and researcher Allan Haverholm, who coined the term Uncomics in his master’s thesis to describe comics that are about abstract and nonlinear modes on the periphery of comics.

Smart Device and Internet of Things (IoT) Convergence Technology Trends

Abstract: Recently, with the rapid spread of smart devices including smartphones, the paradigm of the mobile communication industry is shifting from 'voice call' to 'application', and consumers' perception of information is a process of "development, sharing, participation, and diffusion" I started to pay a lot of attention to the use for personalization and lifestyle change through In particular, due to the recent rise of the Internet of Things (IoT), through interworking with IoT (Internet of Things) and smart devices, we are providing an individual-centered, life-friendly sensor app service that directly processes or controls information collected from nearby sensors. Various attempts are being made to provide it. In this paper, we will look at domestic and international trends in convergence technology with IoT, along with examples of interworking and application of sensors in smart devices.

Industry 4.0-Oriented Turnkey Project: Rapid Configuration and Intelligent Operation of Manufacturing Systems

More extensive personalized product requirements and shorter product life cycles have put forward higher requirements for the rapid establishment, commissioning, and operation of corresponding manufacturing systems. However, the traditional manufacturing system development process is complicated, resulting in a longer delivery time. Many manufacturing enterprises, especially small and micro enterprises, may not have the necessary manufacturing knowledge or capabilities to meet these requirements. Therefore, it is essential to promote the construction of turnkey projects under the paradigm of Industry 4.0, parallelizing and integrating the existing manufacturing system development process based on mass manufacturing equipment to quickly provide turnkey solutions for manufacturing systems’ configuration and implementation for these enterprises. This paper aims to extract and refine the configuration and operation key views of the Industry 4.0-oriented Turnkey Project (I4TP) from Reference Architecture Model Industrie 4.0 (RAMI4.0) and use it to guide the development of key functional processes of turnkey projects to achieve rapid configuration and efficient operation management of manufacturing systems. The turnkey project platform in the Advanced Manufacturing Technology Center (AMTC) is taken as a demonstration case to provide a reference idea for the rapid configuration and intelligent operation of the turnkey manufacturing system.

스마트 제조 국가연구개발 랜드스케이프: 토픽 포트폴리오 및 혁신 주체별 특성

Smart manufacturing, a new paradigm in the manufacturing industry, is leading innovation in the manufacturing industry through the convergence of traditional manufacturing technologies and cutting-edge ICT technologies. This research aims to identify core topics of smart manufacturing in national R&D and uncover the actor-wise characteristics. The 20 R&D topics of smart manufacturing are identified through LDA topic modeling from the research proposals of 3,502 national R&D projects. The identified topics are categorized into five sectors: application, platform, device/network, interoperability/security, and manufacturing R&D. We then propose cooperation strategies between innovation actors to improve smart manufacturing R&D performance. The findings of this study is expected to provide useful implications for policy making in smart manufacturing.

Collaborative Programming for Work-Relevant Learning: Comparing Programming Practice With Example-Based Reflection for Student Learning and Transfer Task Performance

Computer science pedagogy, especially in the higher education and vocational training context, has long-favored the hands-on practice provided by programming tasks due to the belief that this leads to better performance on hands-on tasks at work. This assumption, however, has not been experimentally tested against other modes of engagement such as worked example-based reflection. While theory suggests that example-based reflection could be better for conceptual learning, the concern is that the lack of practice will leave students unable to implement the learned concepts in practice, thus leaving them unprepared for work. In this article, therefore, we experimentally contrast programming practice with example-based reflection to observe their differential impact on conceptual learning and performance on a hands-on task in the context of a collaborative programming project. The industry paradigm of Mob Programming, adapted for use in an online and instructional context, is used to structure the collaboration. Keeping with the prevailing view held in pedagogy, we hypothesize that example-based reflection will lead to better conceptual learning but will be detrimental to hands-on task performance. Results support that reflection leads to conceptual learning. Additionally, however, reflection does not pose an impediment to hands-on task performance. We discuss possible explanations for this effect, thus providing an improved understanding of prior theory in this new computer science education context. We also discuss implications for the pedagogy of software engineering education, in light of this new evidence, that impacts student learning as well as work performance in the future.

Giants with feet of clay: the sustainability of the business models in music streaming services

This paper examines the sustainability of the recorded music industry from the perspective of music performers. Music streaming platforms, or digital music service providers (DMSPs), have changed the recorded music industry paradigm since the middle of the 2010s. Business models for performers have evolved from royalty agreements based on sales to more complex remuneration systems based on revenues from a combination of (ad-based) free and paid subscriptions. Previous research has mainly focused on the examination of the business models of streaming services from the point of view of the innovation players (digital platforms) and/or the traditional dominant intermediaries (record labels and publishers). However, not all innovation-driven transformations are sustainable. In this paper, we argue that the sustainability of the main business models in the music industry demands the consideration of the performers’ perspective. We combine a qualitative approach with primary and secondary data sources to investigate the sustainability of existing trends of business models and business practices for different categories of performers, including both monetary values and a description of how revenues are shared. We conclude that DMSPs foster an asymmetric value chain in which the creative players barely capture value while technology-based innovations increase the capability of DMSPs to generate and capture value. Finally, we outline some alternative business models looking for the long-term sustainability of the digital music marketplace.

89 Meat Science Perspective, Carcass Composition, and Grid Marketing: Have we Made any Advances?

Abstract Throughout recorded history of beef cattle improvement, the pendulum of cattle type has swung from large, old and extremely fat to extremely short in stature and overfinished to extremely tall in stature and lean to moderate in size and overfinished. During all of these transitions, the underlying growth principles of muscle, fat, and bone have remained constant. As animals age, muscle growth, as well as independent accumulation of water and protein increases at a decreasing rate whereas fat growth increases at an increasing rate. Beef carcass grading records reported by USDA indicate that percentage of Prime and Choice grade carcasses increased consistently from 62.9% in 1956 to a peak of 97.7% in 1987. Beginning in 1988, a notable decline in percentage of Prime and Choice began that plateaued from 1997 to 2007; USDA records indicate that Prime and Choice percentage was the lowest in history in 2006 at 59.0%. Since 2007, percentage of carcasses grading Prime and Choice has again steadily increased to 80.7% in 2021. Concomitantly, percentage of carcasses with yield grades of 4 or 5 has increased from a recent low of 1.3% in 1997 to 16.2% in 2021 – the highest percentage of overfinished cattle since records began. The recent improvement in quality is primarily the result of an industry paradigm shift from marketing of live animals and selling beef as a commodity to the marketing of carcasses and selling beef as premium branded products. Cattle feeders have been incentivized to market cattle as carcasses rather than live animals primarily due to the economics associated with carcass transfer. Carcass transfer is the proportion of live animal gain that is retained as carcass gain – this value increases at a decreasing rate during the finishing period and typically ranges from 75 to 85% of live animal gain. Our current yield assessment metric was developed in the late 1950s and is representative of cattle of that period, not modern cattle. The yield grade estimates 40% of the variation in cutability of beef-type cattle carcasses and 0% of the variation in cutability of dairy-type cattle. Opportunity exists to improve beef carcass yield estimation. The goal of our beef production system is to provide domestic and foreign customers with premium quality products that meet their expectations for palatability. Objective shear force values indicate that steaks from the rib and loin have continued to become more tender during the last 3 decades.

The DAWN readiness model to assess the level of use of Industry 4.0 technologies in the construction industry in Brazil

PurposeConstruction industry (CI) has great prominence for the world economy, and it is expected that, with the use of the innovative technologies and approaches of Industry 4.0 (I4.0), the new industrial paradigm, construction can reach higher levels of productivity. This study aims to develop a model (readiness model) to assess the level of use of I4.0 technologies by the construction sector in Brazil and its most relevant applications.Design/methodology/approachThe methodology used was bibliographic research, design-science research and a survey to validate the model, carried out with 162 companies, considered among the main ones in the sector in Brazil. The literature review revealed 13 technologies of I4.0 applied to construction; hence, the views of industry experts were based on these technologies.FindingsThe Digital Advancement Within CoNstruction (DAWN) readiness model was proposed, showing that among the 13 evaluated technologies of I4.0 and their applications, the Brazilian construction companies had a low level of utilization; both high and middle-income companies presented this low level of use; some technologies with a greater number of scientific publications were less used in practice in the Brazilian construction.Originality/valueThe originality and theoretical contribution are to present a readiness model to assess the level of use of I4.0 technologies and their most relevant applications in the CI in countries with an economy similar to Brazil’s, making it possible to measure the level of adoption of these technologies.

Employee-centric innovation: Integrating participatory design and video-analysis to foster the transition to Industry 5.0

Recently, the paradigm of Industry 5.0 has been introduced to complement that of Industry 4.0, which turned out to be technology- rather than human-oriented. Industry 5.0 is meant to foster a transition toward a human-centric industry, where the worker’s well-being is prioritized. To meet this goal, it is crucial to directly involve employees from the earliest stages of design project. In the present work, we describe a case study that was meant to re-design the technology used in a validation laboratory. We adopted a mixed-method approach integrating employee’s self-reported data and objective event-based data from in-the-field video-analysis. By doing this we could build a thorough understanding of the work activities and of the related main issues. We then devised a list of re-design recommendations that were translated in a revised application and in the suggested introduction of portable devices. The outcomes of a preliminary usability evaluation of the revised application were promising, indicating the effectiveness of the methodological approach.

Data Augmentation to Support Biopharmaceutical Process Development through Digital Models—A Proof of Concept

In recent years, monoclonal antibodies (mAbs) are gaining a wide market share as the most impactful bioproducts. The development of mAbs requires extensive experimental campaigns which may last several years and cost billions of dollars. Following the paradigm of Industry 4.0 digitalization, data-driven methodologies are now used to accelerate the development of new biopharmaceutical products. For instance, predictive models can be built to forecast the productivity of the cell lines in the culture in such a way as to anticipate the identification of the cell lines to be progressed in the scale-up exercise. However, the number of experiments that can be performed decreases dramatically as the process scale increases, due to the resources required for each experimental run. This limits the availability of experimental data and, accordingly, the applicability of data-driven methodologies to support the process development. To address this issue in this work we propose the use of digital models to generate in silico data and augment the amount of data available from real (i.e., in vivo) experimental runs, accordingly. In particular, we propose two strategies for in silico data generation to estimate the endpoint product titer in mAbs manufacturing: one based on a first principles model and one on a hybrid semi-parametric model. As a proof of concept, the effect of in silico data generation was investigated on a simulated biopharmaceutical process for the production of mAbs. We obtained very promising results: the digital model effectively supports the identification of high-productive cell lines (i.e., high mAb titer) even when a very low number of real experimental batches (two or three) is available.

BIM implementation: an empirical validation for a four-wheel model

PurposeBecause BIM adoption is still afflicted by various types of hurdles, a complete BIM implementation model is required to provide the necessary methods for driving BIM adoption. As a result, this study looked into the parts of the BIM implementation model that had the most impact on increasing the percentage of BIM adoption in South Africa.Design/methodology/approachThis study developed a four-wheel model of BIM implementation based on implementation process theory, which includes BIM inspiration, BIM capacity development, BIM use and BIM commitment. To assess BIM capacity development, two sub-constructs (BIM learning process and BIM learning methodologies) were used. Two sub-constructs were used to assess BIM utilisation (efficient BIM application and effective BIM application). The sub-constructs employed to quantify BIM motivation were organisational competitiveness, societal conformity and contractual obligations. Incentives, investments and obligations were used to assess BIM commitment. The model was validated using four assumptions and maximum likelihood estimation – structural equation modelling (MLE-SEM).FindingsThe MLE-SEM results demonstrated unequivocally that all of the constructions are critical components of the BIM deployment paradigm in the South African construction industry. BIM motivation, as characterised by organisational competitiveness and social compliance, has the greatest impact. The findings on BIM motivation also revealed that the desire for technological sophistication, competitiveness and social acceptance by clients are encouraging construction organisations and professionals to embrace BIM adoption.Research limitations/implicationsThis study's findings have contributed to the increasing body of literature on BIM deployment. The study has significant implications for achieving BIM implementation in underdeveloped nations where BIM deployment is either non-existent or in its early stages. The theoretical component of the study serves as the foundation for further analysis of BIM deployment.Practical implicationsThis research is important for identifying BIM goals, developing a BIM implementation framework, allocating resources for BIM implementation and defining key performance indicators for BIM implementation. The BIM implementation aspects outlined in this study will be effective in lowering BIM adoption hurdles.Originality/valueThis study makes a unique contribution to BIM research by providing theoretical and empirical analysis into the elements of the BIM implementation model in a developing country. The study offers an excellent opportunity to further our understanding of BIM application in underdeveloped nations.

EsDNN: Deep Neural Network Based Multivariate Workload Prediction in Cloud Computing Environments

Cloud computing has been regarded as a successful paradigm for IT industry by providing benefits for both service providers and customers. In spite of the advantages, cloud computing also suffers from distinct challenges, and one of them is the inefficient resource provisioning for dynamic workloads. Accurate workload predictions for cloud computing can support efficient resource provisioning and avoid resource wastage. However, due to the high-dimensional and high-variable features of cloud workloads, it is difficult to predict the workloads effectively and accurately. The current dominant work for cloud workload prediction is based on regression approaches or recurrent neural networks, which fail to capture the long-term variance of workloads. To address the challenges and overcome the limitations of existing works, we proposed an e fficient supervised learning-based D eep N eural Network ( esDNN ) approach for cloud workload prediction. First, we utilize a sliding window to convert the multivariate data into a supervised learning time series that allows deep learning for processing. Then, we apply a revised Gated Recurrent Unit (GRU) to achieve accurate prediction. To show the effectiveness of esDNN, we also conduct comprehensive experiments based on realistic traces derived from Alibaba and Google cloud data centers. The experimental results demonstrate that esDNN can accurately and efficiently predict cloud workloads. Compared with the state-of-the-art baselines, esDNN can reduce the mean square errors significantly, e.g., 15%. rather than the approach using GRU only. We also apply esDNN for machines auto-scaling, which illustrates that esDNN can reduce the number of active hosts efficiently, thus the costs of service providers can be optimized.

Design and Implementation of OPC UA-Based VR/AR Collaboration Model Using CPS Server for VR Engineering Process

In order to cope with the changing era of the innovative management paradigm of the manufacturing industry, it is necessary to advance the construction of smart factories in the domestic manufacturing industry, and in particular, the 3D design and manufacturing content sector is highly growthable. In particular, the core technologies that enable digital transformation VR (Virtual Reality)/AR (Augmented Reality) technologies have developed rapidly in recent years, but have not yet achieved any particular results in industrial engineering. In the manufacturing industry, digital threads and collaboration systems are needed to reduce design costs that change over and over again due to the inability to respond to various problems and demands that should be considered when designing products. To this end, we propose a VR/AR collaboration model that increases efficiency of manufacturing environments such as inspection and maintenance as well as design simultaneously with participants through 3D rendering virtualization of facilities or robot 3D designs in VR/AR. We implemented converting programs and middleware CPS (Cyber Physical System) servers that convert to BOM (Bill of Material)-based 3D graphics models and CPS models to test the accuracy of data and optimization of 3D modeling and study their performance through robotic arms in real factories.

From Industry 4.0 towards Industry 5.0: A Review and Analysis of Paradigm Shift for the People, Organization and Technology

The industry is a key driver of economic development. However, changes caused by introduction of modern technologies, and increasing complexity of products and production, directly affect the industrial enterprises and workers. The critics of the Industry 4.0 paradigm emphasized its orientation to new technologies and digitalization in a technocratic way. Therefore, the new industrial paradigm Industry 5.0 appeared very soon and automatically triggered a debate about the role of, and reasons for applying, the new paradigm. Industry 5.0 is complementing the existing Industry 4.0 paradigm with the orientation to the worker who has an important role in the production process, and that role has been emphasized during the COVID-19 pandemic. In this research, there is a brief discussion on main drivers and enablers for introduction of these new paradigms, then a literature-based analysis is carried out to highlight the differences between two paradigms from three important aspects—people, organization, and technology. The conclusion emphasizes the main features and concerns regarding the movement towards Industry 5.0, and the general conclusion is that there is a significant change of the main research aims from sustainability towards human-centricity. At the end, the analysis of maturity models that evaluates enterprises’ readiness to introduce features of new paradigms is given as well.

A Multi Objective Evolutionary Algorithm based on Decomposition for a Flow Shop Scheduling Problem in the Context of Industry 4.0

Under the novel paradigm of Industry 4.0, missing operations have arisen as a result of the increasingly customization of the industrial products in which customers have an extended control over the characteristics of the final products. As a result, this has completely modified the scheduling and planning management of jobs in modern factories. As a contribution in this area, this article presents a multi objective evolutionary approach based on decomposition for efficiently addressing the multi objective flow shop problem with missing operations, a relevant problem in modern industry. Tests performed over a representative set of instances show the competitiveness of the proposed approach when compared with other baseline metaheuristics.

Brief exposure to directionally-specific pulsed electromagnetic fields stimulates extracellular vesicle release and is antagonized by streptomycin: A potential regenerative medicine and food industry paradigm

Pulsing electromagnetic fields (PEMFs) have been shown to promote in vitro and in vivo myogeneses via mitohormetic survival adaptations of which secretome activation is a key component. A single 10-min exposure of donor myoblast cultures to 1.5 mT amplitude PEMFs produced a conditioned media (pCM) capable of enhancing the myogenesis of recipient cultures to a similar degree as direct magnetic exposure. Downwardly-directed magnetic fields produced greater secretome responses than upwardly-directed fields in adherent and fluid-suspended myoblasts. The suspension paradigm allowed for the rapid concentrating of secreted factors, particularly of extracellular vesicles. The brief conditioning of basal media from magnetically-stimulated myoblasts was capable of conferring myoblast survival to a greater degree than basal media supplemented with fetal bovine serum (5%). Downward-directed magnetic fields, applied directly to cells or in the form of pCM, upregulated the protein expression of TRPC channels, markers for cell cycle progression and myogenesis. Direct magnetic exposure produced mild oxidative stress, whereas pCM provision did not, providing a survival advantage on recipient cells. Streptomycin, a TRP channel antagonist, precluded the production of a myogenic pCM. We present a methodology employing a brief and non-invasive PEMF-exposure paradigm to effectively stimulate secretome production and release for commercial or clinical exploitation.

Digital-Twin-Aided Product Design Framework For IoT Platforms

The increasing number of products is the trend of current industry. However, the product development process is significantly limited by budget and testing risk. Recently, digital twin (DT) has emerged as a promising industrial paradigm that provides an integrated and cohesive view of the product design process. In this article, we propose a product design framework for Internet of Things (IoT) platforms, namely, DT-aided IoT platform design (DTIPD). This framework considers a large number of IoT devices performing different tasks with machine learning (ML) technologies. Each IoT device constructs a particular ML-based model that deals with its task automatically by feeding related data with labels. The challenges of large-scale network management and ground-truth shortage at the initial stage of product iteration are addressed. We propose a two-level hierarchical learning process using the real-time model status stored at DT servers (DTS), aiming to improve product quality while shortening the development lifecycle. The comprehensive experimental results for both the single-DTS and multiple-DTS scenarios demonstrate the applicability of our framework.

SNMMI Clinical Trials Network Research Series for Technologists: Clinical Research Primer- Use of Imaging Agents in Therapeutic Drug Development and Approval.

The process of bringing a new drug to market is complex and has recently necessitated a new drug discovery paradigm for the pharmaceutical industry that is both more efficient and more economical. Key to this has been the increasing use of nuclear medicine and molecular imaging to support drug discovery efforts by answering critical questions on the pathway for development and approval of a new therapeutic drug. Some of these questions include: (i) Does the new drug reach its intended target in the body at sufficient levels to effectively treat or diagnose disease without unacceptable toxicity? (ii) How is the drug absorbed, metabolized, and excreted? (iii) What is the effective dose in humans? To conduct the appropriate imaging studies to answer such questions, pharmaceutical companies are increasingly partnering with molecular imaging departments. Nuclear medicine technologists are critical to this process as they perform scans to collect the qualitative and quantitative imaging data used to measure study endpoints. This article describes preclinical and clinical research trials and provides an overview of the different ways that radiopharmaceuticals are used to answer critical questions during therapeutic drug development.

Project Management Maturity and Business Excellence in the Context of Industry 4.0

Even though Industry 4.0 is primarily focused on the implementation of advanced digital technologies, this is not the only aspect that should be considered. One of the aspects that calls for attention is the ability to create a sustainable and agile industrial environment. In this sense, the role of project management is crucial for achieving business excellence in a new industrial paradigm. The main goal of this paper was to determine the impact of different levels of project management maturity on business excellence in the context of Industry 4.0. The research in the paper was made using a sample of 124 organizations, differing in industry type and size, and recognized through the business excellence awards or recognitions given by European Foundation for Quality Management (EFQM). Using the Project Management Maturity Model (ProMMM), a significant connection was found between project management maturity and business excellence. Considering technology advances, these relationships were further examined in the context of Industry 4.0. Empirically based conclusions were drawn, which contribute to the literature on project management and business excellence in the context of Industry 4.0. Practitioners can implement them for more effective project management with the intention of bringing excellence into the organization’s operations and results. Additionally, they can be useful to help organizations better cope with changing technology trends.