AI, ML, DT allemaal buzzwoorden die als een soort Haarlemer olie alle problemen oplossen. Hierbij wordt vaak de rol van de mens vergeten. In deze workshop worden de valkuilen van smart technologie implementatie bij productie omgevingen met een hoge varieteit behandeld. Een interessante paradox ontstaat: …

(ca. 61 aanmeldingen, 38 personen geweest, afmeldingen op dag zelf diverse redenen.) Netwerkbijeenkomst Industrie 5.0 georganiseerd door de HAN, Saxion, TNO en Universiteit Twente. Momenteel zien we veel veranderingen in de maakindustrie op het gebied van technologische innovatie, veranderende beroepsbevolking …

This paper presents a Decision Support System (DSS) that helps companies with corporate reputation (CR) estimates of their respective brands by collecting provided feedbacks on their products and services and deriving state-of-the-art key performance indicators. A Sentiment Analysis Engine (SAE) is at …

Data-driven condition-based maintenance (CBM) and predictive maintenance (PdM) strategies have emerged over recent years and aim at minimizing the aviation maintenance costs and environmental impact by the diagnosis and prognosis of aircraft systems. As the use of data and relevant algorithms is essential …

Recently, the job market for Artificial Intelligence (AI) engineers has exploded. Since the role of AI engineer is relatively new, limited research has been done on the requirements as set by the industry. Moreover, the definition of an AI engineer is less established than for a data scientist or a software …

In my previous post on AI engineering I defined the concepts involved in this new discipline and explained that with the current state of the practice, AI engineers could also be named machine learning (ML) engineers. In this post I would like to 1) define our view on the profession of applied AI engineer …

This chapter discusses how to build production-ready machine learning systems. There are several challenges involved in accomplishing this, each with its specific solutions regarding practices and tool support. The chapter presents those solutions and introduces MLOps (machine learning operations, also …

The past two years I have conducted an extensive literature and tool review to answer the question: “What should software engineers learn about building production-ready machine learning systems?”. During my research I noted that because the discipline of building production-ready machine learning systems …

In this work, the concept of an Artificial Intelligence-based (AI) Digital Twin (DT) of an aircraft system is introduced, with the goal to improve the corresponding MRO Operations. More specifically, the current study aims to obtaining knowledge on the optimal placement of sensors in an ideal Power Electronics …

The current set of research methods on ictresearchmethods.nl contains only one research method that refers to machine learning: the “Data analytics” method in the “Lab” strategy. This does not reflect the way of working in ML projects, where Data Analytics is not a method to answer one question but the …