QFD Approach for Integrated Information and Data Management Ecosystem: Umbrella Modelling Through Internet of Things

Author(s):  
Arindam Chakrabarty ◽  
Tenzing Norbu
2020 ◽  
pp. 89-103
Author(s):  
Amrit Sahani ◽  
Ranjit Kumar ◽  
Suchismita Chinara ◽  
Anjali Kumari ◽  
Bina Patro

Author(s):  
Reinhard Heister ◽  
Reiner Anderl

Workflows to produce dental products by using CAD/CAM technology are very complex. Each patient needs an individual restoration. The challenge is to provide a patient individual production aiming at a price of mass production. But every single job has to run through an individual development as well manufacturing process. Typically, three stakeholders are involved in the workflow. The dentist performs the treatment and defines requirements for restoration. The dental laboratory plans the workflow and designs the reconstruction by using a dental CAD system. Subsequently, a milling center produces the restoration. Because of these highly heterogeneous workflows, diverse data streams and incompatibilities result. Often improper partners and resources are involved in the workflow. This fact is a significant source for errors. An additional complication is that errors are often discovered in late phases of the workflow. To avoid high costs and unacceptable delivery times, the aim is to develop a new concept for integrated workflow planning. The concept depends on three parts: Federative dental data management (FDDM) as a basic approach, including anticipated logic and structured activities. The federative data management provides a loosely coupling of heterogeneous systems crossing enterprise borders by using web technology. The FDDM service depends on APP technology. Each participant applies its specialized APP: FDDMz (dentist), FDDMd (dental laboratory) and FDDMf (milling center). FDDM services enable a continuously integrated workflow throughout the whole process of a patient individual production. Each participating enterprise is able to register its available processes and resources. Information about resources like 3D dental scanner or milling machines are able to add, according to a global data model schema. This schema depends on an integrated information model with eight partial models: Collaboration, resource, process, workflow, requirements, product, work preparation and production model. This integrated information model provides dental information including interlinked objects. Through a proper anticipation logic, conclusions about later phases can be anticipated already at early phases. The last conceptual part is workflow management on frame of structured activities. By combining the information network with the anticipation logic, filtering of appropriate partners, processes, resources and sequences is supported. Next, a prototypical implementation is demonstrated exemplarily. This concept delivers an important contribution to increase process reliability and quality as well as to reduce delivery times and costs for digital dental workflows.


2017 ◽  
Vol 62 (2) ◽  
Author(s):  
Martin Forstner

AbstractThe Internet of things will influence all professional environments, including translation services. Advances in machine learning, supported by accelerating improvements in computer linguistics, have enabled new systems that can learn from their own experience and will have repercussions on the workflow processes of translators or even put their services at risk in the expected digitalized society. Outsourcing has become a common practice and working in the cloud and in the crowd tend to enable translating on a very low-cost level. Confronted with promising new labels like


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