A survey of visualization for smart manufacturing

Zhou, Fangfang; Lin, Xiaoru; Liu, Chang; Zhao, Ying; Xu, Panpan; Liu, Ren; Xue, Tingmin; Ren, Lei

doi:10.1007/s12650-018-0530-2

Cited by 95 publications

(35 citation statements)

References 73 publications

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“…Daher wird eine direkte Verbindung zwischen explorativen, computerbasierten Entwurfsoptimierungs‐ und Visual‐Analytics‐Methoden angestrebt [28], und zwar sowohl von neuartigen, hochleistungsfähigen Bausystemen als auch von deren effizientem Aufbau durch durchgängige 4‐D‐Modellierung (räumliche Dimensionen in Verbindung mit der Zeit) und die Nutzung künstlicher Intelligenz [29] und der explorativen Datenvisualisierung. In vielen Bereichen der industriellen Produktion werden schon Visualisierungsmethoden erfolgreich eingesetzt [30], jedoch bringt die 4‐D‐Modellierung im Bauen besondere Herausforderungen mit sich [31]. Ein Ziel ist dabei auch, die spezifischen Eigenheiten fortschrittlicher Fertigungs‐ und Materialtechnologie zur Anpassung an Kräfte in mehreren Skalen zu berücksichtigen.…”

Section: Co‐design In Forschungsnetzwerkenunclassified

Integratives computerbasiertes Planen und Bauen: Architektur digital neu denken

et al. 2021

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Die Herausforderung an das Bauen der Zukunft besteht darin, mehr zu bauen, dabei weniger Schadstoffe zu emittieren und weniger endliche Ressourcen zu verbrauchen und trotzdem eine qualitätsvolle und lebenswerte gebaute Umwelt zu schaffen. In einem sich wechselseitig beeinflussenden Prozess müssen hierfür sowohl die Produktivität der Bauprozesse als auch die Energie‐ und Ressourceneffizienz der Bausysteme verbessert werden. Digitale Technologien bieten neue Lösungsansätze für diese Herausforderungen. Ziel des Exzellenzclusters IntCDC an der Universität Stuttgart und dem Max‐Planck‐Institut für Intelligente Systeme ist es, das volle Potenzial digitaler Technologien zu nutzen, um das Planen und Bauen in einem integrativen und interdisziplinären Ansatz neu zu denken und damit die methodischen Grundlagen für eine umfassende Modernisierung des Bauschaffens zu legen. Eine zentrale Zielsetzung ist die Entwicklung einer übergeordneten Methodologie des „Co‐Design“ von Methoden, Prozessen und Systemen, basierend auf interdisziplinärer Forschung zwischen den Bereichen Architektur, Bauingenieurwesen, Ingenieurgeodäsie, Produktions‐ und Systemtechnik, Informatik und Robotik sowie Geistes‐ und Sozialwissenschaften. So sollen Lösungswege für die ökologischen, ökonomischen und sozialen Herausforderungen aufgezeigt und die Voraussetzungen für eine qualitätsvolle, lebenswerte und nachhaltige gebaute Umwelt sowie für eine digitale Baukultur geschaffen werden.

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Section: Co‐design In Forschungsnetzwerkenunclassified

Integratives computerbasiertes Planen und Bauen: Architektur digital neu denken

et al. 2021

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“…Digital technologies engineer human error out of the production system and enable shopfloor employees to perform their respective tasks in an improved and more efficient manner (Lazarevic et al 2019). Embedded applications provide continuous feedback about successful task execution (Longo et al 2017) and/or about the status of the production process (Zhou et al 2019 ' (2019: 140). Work intensification originates in that digital technologies both allow for and require the enhancement of lean practices as well as the optimising and standardising of work (Buer et al 2018, Wagner et al 2017.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Decision-making for production planners and schedulers is supported by smart algorithms integrated in the cyberphysical production systems (Colledani et al 2014) that perform real-time optimisation. Accordingly, the shopfloor engineers engaged in process optimisation, who used to rely on accumulated experiences and tacit knowledge to identify and eliminate bottlenecks and other process vulnerabilities, now rely on machine learning-powered process management algorithms that identify the best procedural approaches and recommend actions (D'Addona et al 2018;Romero et al 2016;Zhou et al 2019).…”

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confidence: 99%

Digital technologies and the nature and routine intensity of work: Evidence from Hungarian manufacturing subsidiaries

Szalavetz

2021

SSRN Journal

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This paper explores the impact of digital technologies on the nature and routine intensity of shopfloor work, the ways in which digital technologies exert their effects and the factors moderating the outcomes of digitalisation in respect of work.The effect of technology cannot be limited to a dichotomy of increasing versus decreasing degrees of routine. Instead, there are basic scenarios as far as the routine content of activities is concerned: a) no change in routine; b) increased routine; c) transformed routine; d) reduced routine.More specifically, drawing on data from Hungarian companies, we discuss the multiple ways that technology affects the nature and routineness of work. These include (i) workload and intensity of work; (ii) the degree to which tasks can be explicitly defined, measured and codified; (iii) task spectrum, i.e. the variability, complexity and diversity of work tasks; (iv) the composition and amount of skills required for task execution; (v) the importance of experience or tacit knowledge for task execution; and (vi) the value added of work tasks.Evidence indicates that the qualitative enrichment of shopfloor work and digital technology-induced reduction in the routine content of job tasks apply only to relatively skilled employees, albeit not exclusively in high-level shopfloor functions. It is argued that the beneficial effects of digital technologies materialise only if employees are skilled enough to be upskilled and become engaged not only in digitally-assisted but also in digitally-augmented, high-value activities.Finally, positive developments in the nature of work require that employees' work tasks be reorganised, work design and work practices modified and employees upskilled: thus, they are contingent on conscious organisational and human resources management.Without these intentional managerial interventions, digital technology implementation entails deskilling and/or technological unemployment rather than providing richer dimensions to shopfloor work. Digital technologies and the nature and routine intensity of work WP 2021.01 5 Digital technologies and the nature and routine intensity of work WP 2021.01 9

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“…In summary, we present the first attempt to understand the perceptual bias of scatterplots caused by geometric scaling. We contribute a carefully designed evaluation and a series of instructive findings, which may bring new considerations to the design decisions of scatterplots in various creation, exploration, and sharing scenarios [41,74,84,85].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Perceptual Bias During Geometric Scaling of Scatterplots

Wei

Mei

Zhao

et al. 2020

IEEE Trans. Visual. Comput. Graphics

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Scatterplots are frequently scaled to fit display areas in multi-view and multi-device data analysis environments. A common method used for scaling is to enlarge or shrink the entire scatterplot together with the inside points synchronously and proportionally. This process is called geometric scaling. However, geometric scaling of scatterplots may cause a perceptual bias, that is, the perceived and physical values of visual features may be dissociated with respect to geometric scaling. For example, if a scatterplot is projected from a laptop to a large projector screen, then observers may feel that the scatterplot shown on the projector has fewer points than that viewed on the laptop. This paper presents an evaluation study on the perceptual bias of visual features in scatterplots caused by geometric scaling. The study focuses on three fundamental visual features (i.e., numerosity, correlation, and cluster separation) and three hypotheses that are formulated on the basis of our experience. We carefully design three controlled experiments by using well-prepared synthetic data and recruit participants to complete the experiments on the basis of their subjective experience. With a detailed analysis of the experimental results, we obtain a set of instructive findings. First, geometric scaling causes a bias that has a linear relationship with the scale ratio. Second, no significant difference exists between the biases measured from normally and uniformly distributed scatterplots. Third, changing the point radius can correct the bias to a certain extent. These findings can be used to inspire the design decisions of scatterplots in various scenarios.

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A survey of visualization for smart manufacturing

Cited by 95 publications

References 73 publications

Integratives computerbasiertes Planen und Bauen: Architektur digital neu denken

Integratives computerbasiertes Planen und Bauen: Architektur digital neu denken

Digital technologies and the nature and routine intensity of work: Evidence from Hungarian manufacturing subsidiaries

Evaluating Perceptual Bias During Geometric Scaling of Scatterplots

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