Industry 4.0 means updating manufacturing and supply chain management with digital tools and smart systems. It is more than just traditional automation. It uses technologies like the Internet of Things (IoT), artificial intelligence (AI), blockchain, cloud computing, and big data. These technologies work together to create smart factories, smart supply chains, and smart products. They respond faster and more accurately to changes.
These technologies make healthcare supply chains and manufacturing more flexible, efficient, and quick to respond. Studies by IBM show smart manufacturing can reduce production errors by up to 50% and increase output by 20%, which shows the benefits of Industry 4.0.
Healthcare providers and medical practice managers in the United States face tough challenges managing supply chains that provide medical supplies, medicines, and equipment. Any delay or problem can affect patient care and costs.
AI-powered systems improve supply chains by:
Research by KPMG says that by 2024, half of supply chain groups in the US will heavily use AI and advanced analytics to make operations better. This shows that many parts of healthcare want to improve using these technologies.
Medical product manufacturing in the US is changing a lot with Industry 4.0 technologies. Combining AI, IoT, and robotics helps makers of medical devices, equipment, and medicines to meet demand while keeping good quality.
Important improvements include:
This move to smart manufacturing relies on hybrid multicloud systems that process large amounts of data safely and flexibly, as IBM points out. For smaller and medium healthcare manufacturers, cloud computing lowers technology costs and helps adopt digital tools faster.
One of the key uses of AI in healthcare and manufacturing is automating routine tasks. Automating simple, rule-based work frees staff from manual tasks, lowers errors, and speeds up work. This is important in medical practices where paperwork and admin can affect patient care.
Key areas where AI helps automate workflows are:
By using automated workflows, healthcare managers and IT leaders in the US can get more done with less admin work and fewer risks.
Industry 4.0 technologies do not just improve efficiency. They also help meet sustainability goals. In US healthcare, improving supply chains and manufacturing lowers waste, uses less energy, and supports care for the environment.
At the same time, these changes help social fairness. AI-driven scheduling and supply chain models help make sure healthcare reaches underserved groups and reduces care differences.
Using IoT, blockchain, big data, and AI in US healthcare brings benefits, but also challenges:
Good management of these issues, with teamwork among healthcare leaders, IT teams, and tech providers, is needed to use these innovations well.
Experts say that combining AI technology with real-world knowledge is important for success. Peter Liddell from KPMG in Singapore notes that success depends on a culture of good decisions backed by technology systems and partnerships with universities.
Dr. Vahid Sohrabpour says that using Industry 4.0 technologies such as IoT, cloud computing, blockchain, big data, and AI forms the base for smarter supply chains and manufacturing. This allows real-time choices, quick responses, and strong operations. These are very important for healthcare providers in the United States to meet the growing needs of patients efficiently.
By learning about and using these technologies, medical practice managers, owners, and IT teams in the United States can make their supply chains and manufacturing smarter, stronger, and better suited to changing healthcare needs. This digital change helps improve patient care and supports ongoing operations across healthcare.
The paper aims to identify the contributions of artificial intelligence (AI) to supply chain management (SCM) by systematically reviewing existing literature to address current scientific gaps and suggest potential AI techniques for improving SCM.
The study covers (1) prevalent AI techniques in SCM, (2) potential AI techniques for SCM, (3) current AI-enhanced SCM subfields, and (4) subfields with high potential to be improved by AI.
The paper employs a systematic literature review using specific inclusion and exclusion criteria to identify and examine papers across four SCM fields: logistics, marketing, supply chain, and production.
Key researchers include Reza Toorajipour (business model innovation, SCM), Dr. Vahid Sohrabpour (Industry 4.0 technologies, IoT, AI in SCM), Dr. Ali Nazarpour (operations and supply chain management), and Dr. Pejvak Oghazi (business studies and industrial marketing).
He worked in the construction sector and automotive industry holding roles such as Sales Supervisor, Marketing and Sales Planning Chief, and Inventory Management Project Manager.
He integrates Internet of Things (IoT), Cloud Computing, Block Chain, Big Data, and Artificial Intelligence to promote Smart Supply Chain, Smart Manufacturing, and Smart Products.
AI can improve efficiency, optimization, and decision-making within SCM processes by analyzing large data sets, forecasting demands, and automating logistics, which traditional methods may struggle to handle effectively.
The four SCM fields analyzed are logistics, marketing, supply chain, and production.
The paper identifies scientific gaps that require further research to better understand and implement AI techniques effectively across various SCM subfields.
It synthesizes and analyzes current knowledge to provide insights on effective AI techniques, enabling academics and practitioners to understand which AI methods are most beneficial to specific SCM subfields and where future research should focus.
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