Manufacturers are no strangers to automation. Since the first steam-powered machines, the manufacturing industry has focused on providing better products – and particularly through automating processes, lowering operating costs, and boosting quality for more than 50 years. Recently it was reported in a survey on AI adoption in manufacturing revealing that 93 percent of companies believe AI will be a crucial technology to drive growth and innovation. But, as the industry expands its use of AI, it also faces growing challenges of shorter time-to-market deadlines, increasingly complex products, and strict quality regulations and standards.
Organizations across all industries are discovering that experienced data scientists and AI professionals are scarce and difficult to hire. AI projects require an interdisciplinary team of data scientists, ML engineers, software architects, and BI analysts and SMEs. Many businesses do not have and cannot afford to deploy these resources for a single data-science project. And, when you have multiple data-science projects to execute, it becomes even more difficult to scale to deliver on time. An ecosystem that offers compatible components that use standard rules and frameworks to connect to ERP, MES, and PLC/SCADA systems will address issues with interoperability. OPA UA is becoming the essential protocol for Industry 4.0 communication and data modelling.
While most AI traditionally uses ‘black box’ models, new approaches to data science provide more transparency into the full AI pipeline. This includes insight into the detailed process to transform the raw data into the inputs of machine learning and how the ML model produces predictions by combining hundreds of or even more features. By giving insight about how the prediction models work and the reasoning behind predictions, manufacturing organizations can build greater trust in the models and resulting business insights produced.
Central to a successful AI program is deploying a data-science automation platform that can integrate seamlessly with your current systems and solutions, and can automate the full data science life-cycle, freeing SMEs to focus on the results of your AI and machine learning applications, not the headaches of the data science process.
We present to you, “Top 10 Manufacturing Intelligence Solution Providers - 2021.”
