Bøger af Jagdeep Singh

In den letzten Jahren hat die Gesundheitsbranche riesige Mengen von Gesundheitsdaten gesammelt, die leider nicht extrahiert werden, um verborgene Informationen für eine effektive Entscheidungsfindung zu entdecken. Die medizinischen Dienste haben heute einen langen Weg zurückgelegt, um Patienten mit verschiedenen Krankheiten zu behandeln. Eine der tödlichsten ist die Herzerkrankung, die mit bloßem Auge nicht zu erkennen ist und sofort auftritt. Die Sterblichkeitsrate ist aufgrund schlechter klinischer Entscheidungen gestiegen. Um eine zuverlässige und kosteneffiziente Behandlung zu erreichen, können computergestützte Informations- oder Entscheidungshilfesysteme entwickelt werden, die diese Aufgabe übernehmen. Data Mining bietet die Lösung für die Entdeckung von Wissen aus diesen großen und komplexen Datenbanken. Die Arbeit des Autors umfasst die Entwicklung eines Rahmens, der auf assoziativen Klassifizierungstechniken für Herzdaten basiert. Die Implementierung der Arbeit erfolgt auf dem Herzdatensatz aus dem UCI Machine Learning Repository, um verschiedene Methoden zu testen und zu bewerten, um bessere Ergebnisse zu erzielen. Die experimentellen Ergebnisse zeigen, dass die meisten assoziativen Klassifizierungsregeln die beste Vorhersage von Herzerkrankungen ermöglichen und zu einem zuverlässigen Entscheidungshilfesystem beitragen.

Au cours des dernières années, le secteur des soins de santé a collecté d'énormes quantités de données qui, malheureusement, ne sont pas extraites pour découvrir des informations cachées permettant une prise de décision efficace. Aujourd'hui, les services médicaux ont parcouru un long chemin pour traiter les patients atteints de diverses maladies. L'une des plus mortelles est la maladie cardiaque, qui ne peut être vue à l'oeil nu et survient instantanément. Le taux de mortalité a augmenté en raison de mauvaises décisions cliniques. Pour parvenir à un traitement fiable et rentable, des systèmes d'information ou d'aide à la décision basés sur l'informatique peuvent être développés pour accomplir cette tâche. L'exploration de données fournit la solution pour la découverte de connaissances à partir de ces bases de données vastes et complexes. Le travail de l'auteur implique le développement d'un cadre basé sur des techniques de classification associative sur un ensemble de données cardiaques. La mise en oeuvre du travail est effectuée sur l'ensemble de données cardiaques de l'UCI Machine Learning Repository afin de tester et d'évaluer différentes méthodes pour obtenir de meilleurs résultats. Les résultats expérimentaux montrent que la plupart des règles de classification associative aident à la meilleure prédiction des maladies cardiaques et à la création d'un système d'aide à la décision fiable.

Negli ultimi anni l'industria della sanità raccoglie enormi quantità di dati sanitari che, purtroppo, non vengono estratti per scoprire informazioni nascoste per un processo decisionale efficace. Oggi i servizi medici hanno fatto molta strada per curare i pazienti affetti da varie malattie. Tra le più fatali c'è la cardiopatia, che non può essere vista a occhio nudo e si manifesta all'istante. Il tasso di mortalità è aumentato a causa di decisioni cliniche sbagliate. Per ottenere un trattamento affidabile e conveniente si possono sviluppare sistemi di informazione o di supporto alle decisioni basati su computer. Il data mining fornisce la soluzione per la scoperta della conoscenza da questi grandi e complessi database. Il lavoro dell'autore prevede lo sviluppo di un framework basato su tecniche di classificazione associativa su dataset cardiaci. L'implementazione del lavoro è stata effettuata su un set di dati cardiaci provenienti dall'UCI Machine Learning Repository per testare e valutare i diversi risultati. I risultati sperimentali mostrano che la maggior parte delle regole di classificazione associativa aiutano a prevedere meglio le malattie cardiache e a creare un sistema di supporto decisionale affidabile.

Nos últimos anos, o sector da saúde tem recolhido enormes quantidades de dados sobre cuidados de saúde que, infelizmente, não são extraídos para descobrir informações ocultas que permitam uma tomada de decisão eficaz. Atualmente, os serviços médicos percorreram um longo caminho para tratar doentes com várias doenças. Uma das mais fatais é a doença cardíaca, que não pode ser vista a olho nu e surge instantaneamente. As taxas de mortalidade aumentaram devido a más decisões clínicas. Para conseguir um tratamento fiável e rentável, podem ser desenvolvidos sistemas de informação ou de apoio à decisão baseados em computador. A extração de dados fornece a solução para a descoberta de conhecimentos a partir destas grandes e complexas bases de dados. O trabalho do autor envolve o desenvolvimento de uma estrutura baseada em técnicas de classificação associativa no conjunto de dados do coração. A implementação do trabalho é efectuada no conjunto de dados sobre o coração do Repositório de Aprendizagem Automática da UCI para testar e avaliar diferentes para obter melhores resultados. Os resultados experimentais mostram que a maioria das regras de classificação associativa ajuda a prever melhor as doenças cardíacas e a criar um sistema fiável de apoio à decisão.

"Cost Saving Ideas in Supply Chain Management" is part of the "Cost Saving Bible" series, which helps firms, cut costs and boost efficiency in their supply chains. Supply chain management is complicated, with many players involved in ensuring the smooth movement of goods and services. However, with the correct tactics and procedures, firms can achieve significant cost savings while retaining good quality. Sections cover diverse supply chain management topics.I, Dr. Jagdeep Singh at Recap Consultancy and General Supply, understand that every business is different, thus I offer customized solutions to match industry needs. I help companies streamline their supply chains, cut expenses, and succeed. My book will inspire and motivate firms to take bold strides toward efficiency, profitability, and global competitiveness. I think cutting money doesn't entail cutting quality or service. Cost-saving initiatives help organizations operate better and satisfy customers with less.This book provides practical advice and examples, and it will help business owners and supply chain professionals save costs.

Doctoral Thesis / Dissertation from the year 2020 in the subject Business economics - Business Management, Corporate Governance, grade: 75.00, , course: Doctor of Philosophy, language: English, abstract: In this research, SCM practices in automobile industry in India were a descriptive cum analytical research. It needs an understandable specification of who (automobile companies in India), what (SCM practices ¿ SRM, CRM, LM and ICT), when (until year 2019), why (found gaps) and way (survey- questionnaire, F2F Interview, through email) of the research. The figure-50 has shown the brief research design of the study. During the literature review, it was found that Indian automobile companies were not able to minimize their supply chain cost effectively & efficiently and there were gaps in expectations (agreement) and perception (adoption) level of SCM practice. To understand and analyses these gaps, this research was carried out. Indian automotive industry (Both automobile & components) contributes almost 7.5% of total GDP and one of the biggest job creator sectors directly or indirectly. India is gradually taking the lead and growing its global competition. India is lagging behind in terms of commercial vehicle production if we compare it globally, therefore, it needs more focus, collaborations and investment to catch up the market share at global space. SCM contributes to overall value creation for any organization including automobile and hence firms are focusing on strengthening their supply chains more efficient and competitive. Current supply chains are facing multiple disruptions like Covid-19 pandemic, technological disruptions like 3D Printing, IoT, AI/machine learning, internet things such as movable machine (robots) for warehouse operation, etc. and challenges such as visibility, cost reduction, innovation, supplier relationship, customer relationship, risk management, security & safety in logistics, ICT infrastructure, and customer expectations.

In the contemporary automotive manufacturing industry, service providers are continuously working to improve system optimization in order to remain competitive in the market and deliver quality products to satisfy their customers. With this comes the possibility of failure, rejection and reworking of the components or services in the system, which can incur high costs and impact the reputation of an organization. This book uses Failure Mode and Effect Analysis (FMEA) to assess, investigate and predict the Risk Priority Number (RPN) of potential failures for three companies within the manufacturing industry:A metal component supplier in the automotive sectorPart manufacturer for the automobile and engineering industriesManufacturer of suspension components for commercial vehiclesIntegrating human expertise and artificial intelligence on a single platform, the authors use fuzzy logic as a tool to overcome the vagueness associated with traditional methods of assessing potential failures. The book also details the procedure and scales of how to conduct FMEA, offering guidance on how to input and rank each risk within manufacturing processes across a range of sectors's. Each of the three real-world cases offer suggested improvements for the companies themselves, alongside takeaways for researchers and professionals within the fields of manufacturing and supply chain management.

Modern Manufacturing Organizations are applying advanced manufacturing technologies like Just-in ¿Time philosophy in Manufacturing and to enhance the manufacturing operations through process modification. The right time delivery of the product is important for this organization to retain itself in competitive world. Some JIT practices are capable of performing through strategic implementation towards manufacturing performance improvement. JIT means what and when the costumer want .So, as the literature suggests there is lot of work done on JIT approach level but research is still lacking to check the performance at strategic level or at the level of importance of different JIT practice in the manufacturing organizations in Punjab. So an attempt has been made to determine impact of strategic implementation of JIT practices and its impact on manufacturing performance in manufacturing industry of Punjab. The performance of manufacturing strategies like JIT needs to be accessed at strategic level.Modern Manufacturing Organizations are applying advanced manufacturing technologies like Just-in ¿Time philosophy in Manufacturing and to enhance the manufacturing operations through process modification. The right time delivery of the product is important for this organization to retain itself in competitive world. Some JIT practices are capable of performing through strategic implementation towards manufacturing performance improvement. JIT means what and when the costumer want .So, as the literature suggests there is lot of work done on JIT approach level but research is still lacking to check the performance at strategic level or at the level of importance of different JIT practice in the manufacturing organizations in Punjab. So an attempt has been made to determine impact of strategic implementation of JIT practices and its impact on manufacturing performance in manufacturing industry of Punjab. The performance of manufacturing strategies like JIT needs to be accessed at strategic level.

Chapter 4 presents a detailed survey to determine the present status of continuous improvement strategies in the Indian manufacturing industry, to assess the important barriers that effect the implementation of CI strategies, and to also assess the role of key enablers leading to improve the performance of manufacturing operations.