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Artificial Intelligence (AI), and the Internet of Things (IoT) are increasingly becoming mainstream in the manufacturing industry. What is perhaps less understood is the degree to which these technologies are converging.
AI takes manufacturers to the next level by leveraging the data collected by the IIoT. Given all this, it makes sense to begin thinking about the next concept – the AIoT – the Artificial Intelligence of Things.
Leveraging AI and IIoT to optimize the decision flow from planning to execution in aerospace composites manufacturing
Manufacturers working with composites in the aerospace industry face a series of unique and complex challenges. These include the time-sensitive nature of many composite raw materials that require constant monitoring. The Plataine partnership represents a major step forward for Siemens’ aerospace customers, delivering new levels of material savings and manufacturing efficiencies that are tailored specifically to the needs of factories working with composites.
The benefits of the cloud software solutions include lower IT costs, allowing teams (and even whole factories) to collaborate like never before; giving factories the chance to benefit from the Software as a Service (SaaS) business models that are becoming more popular every day; and delivering the remote deployment and remote working capabilities that have become so necessary in the COVID-19 era.
In today’s complex-manufacturing competitive landscape there’s no room to make critical mistakes. Following over a decade of close collaborations with top discrete manufacturing players, we’ve come to know and learn to spot some of the most widespread mistakes. This article looks at the common pitfalls and examines top manufacturers’ strategies to avoid them.
The unique challenges of composite part manufacturing such as the limited shelf-life of raw composite materials and strict quality requirements– elevate the potential benefits of IIoT based technology. COVID-related disruptions are further accelerating Digital Transformation, as manufacturers seek to increase resiliency, flexibility, and profitability. It all starts with increased production floor visibility, also creating the foundation for optimized, flexible production operations.
10 Questions Discrete Manufacturers Must Ask Before Choosing an Industrial IoT Solution for Their Connected Factory
While the decision to implement an IIoT / connected factory / Industry 4.0 solution is a no brainer, choosing and onboarding the right IIoT provider and the right solution remains a big challenge.
There’s no better time than now to put together a digital transformation plan and start looking for the right supplier.
When a new year begins it’s time for us to create our annual trend list. Even when a pandemic hits out of the blue, manufacturers who were relatively resilient and were already embracing the latest technologies, found it easier to adjust and respond. In an uncertain climate like today’s, the next lines offer a clear direction for prioritization and development.
May the force be with you, manufacturers: Emerging workforce challenges, trends and winning strategies in today’s remote work age
The challenges manufacturers encounter during these times take on many forms Some challenges lead to new strategies that will stick along as they create an opportunity for companies and prevail for that reason.
In this article, I will focus on changes related to the professional manufacturing workforce that will probably stick around.
Production scheduling in the Industry 4.0 era – AI-based Digital Assistants can provide vital support
Scheduling production operations is one of the key challenges faced by planners and schedulers working for advanced manufacturers. An optimized production schedule will improve on time delivery while ensuring the best possible use of factory floor resources – increasing throughput and reducing waste. AI-based intelligent software can help planners meet their objectives.
A new standard for lean manufacturing? How cutting optimization increases the entire manufacturing organization’s profitability
Optimized cutting and kitting processes in many discrete manufacturing segments are crucial due to the high cost of raw materials, and therefore they have a direct influence on the company’s overall profitability. Manufacturers are leaning on technology to optimize every step in the process. AI technology helps meet manufacturing needs by offering a dramatic advancement in cut planning and manufacturing optimization.
When the word ‘AI’, enters the discussion things become interesting. “Oh, we already use AI,” people say to me.
I’m always happy to indulge in conversations about AI use cases, so I immediately ask if they would be OK with telling me a little about their system, and how exactly it’s being used.
Then, as the discussion continues, it becomes clear that they were actually referring to BI, reports and dashboards and not AI in the deep sense that I was.
Don’t confuse AI with data analysis and dashboards
The digital manufacturing transformation is continuing to grow at full speed. As it is a part of a cross industry shift, specifically in the advanced manufacturing industry, enterprises deal with crucial and expensive procedures.
SME & Plataine surveyed the market to identify important Industry 4.0 trends in 2020. We compared the findings to trends we’ve identified in our last survey that we ran in 2018, and we published an industry report that presents and highlights our most important findings. As you will soon read, a lot has changed over the course of 2 years.