Intelligent factory solutions integrate your operational, maintenance, and planning business systems for optimized cost optimization. This enables them to identify machine failures prior to incurring downtime expenses; predict machine failures before they happen; prevent costly downtime delays and boost productivity – ultimately improving productivity by eliminating wasteful downtime costs and improving machine uptime rates.
Data analysis is key in this regard, as disparate sets can be aggregated and evaluated to identify opportunities and risks, optimize performance, and auto-correct as necessary.
AI & Machine Learning
AI is used for many different tasks today, from image recognition and language processing, detecting fraud and optimizing inventory to automating processes, cutting costs and providing more tailored content.
ML on the other hand is more focused; its goal is to identify patterns within data and learn how best to utilize it for a specific task, like machine breakdown predictions or product quality evaluation. As a result, ML algorithms are capable of making better predictions in regards to future events such as machine breakdown or product quality evaluation.
Smart factory solutions require a modern database that can process massive amounts of real-time information generated by smart systems, then analyze this data using AI/ML algorithms for actionable insights to be delivered by business leaders or even make autonomous decisions on its own. To achieve this, in-memory data platforms or scalable ERP systems may be appropriate solutions.
Big Data Analytics
At this level, data collected from a smart factory is collected and analysed using an advanced data management system. With its insights gained, problems can be quickly solved or improvements initiated without human involvement.
For instance, when an IoT sensor detects impending machine failure, its smart system can notify its operator so that maintenance can be scheduled immediately to avoid downtime and enable predictive quality assurance based on real-world data.
Finalizing these recommendations requires giving employees the means to act upon them, which is where augmented and virtual reality come into play – both offering novel ways of accessing data and improving workflows.
First step to creating a smart factory: consolidating and analyzing operational data cost-effectively without much human involvement. Thanks to modern data management technology, this can now be accomplished cost-efficiently and without excessive human involvement.
Smart factories utilise interconnected equipment, integrated applications, big data analytics and cutting-edge technologies to achieve high levels of automation and flexibility on both production floors and supply chains. Their system can adapt instantly to issues, problems or changes within its supply chains.
The insights uncovered from data mining can trigger workflows to automate maintenance tasks or notify personnel when action needs to be taken. For instance, when news of increased demand for a specific product emerges in the media, 3D printer workflows could be instructed to increase production priority accordingly. Success lies in aligning all intelligent systems with business processes while empowering employees to act upon it – this requires taking an adaptive digital transformation strategy with five key capabilities in mind.
An integrated smart factory integrates automation, interconnected systems and big data for increased levels of efficiency, flexibility and autonomous operation. All systems must be capable of accessing, connecting and analyzing information across the production facility – often necessitating investments in new technology as well as increased wireless and wired connectivity as well as sensors.
Data Analysis: Machine learning and intelligent business systems utilize advanced analytics and modern data management solutions to make sense of the vast amount of information generated by connected devices on the shop floor. IIoT sensors can warn when machines require servicing or repairs; market and operational data can help identify opportunities or risks; workflow efficiency studies over time can reveal issues which require correction; all these aspects combine together for meaningful analysis.
Smart factory capabilities are a powerful way to reduce operational costs, improve production quality and increase revenue. But in order to fully take advantage of its potential, employees need access to actionable data and be empowered to act. NetSuite provides manufacturers with a complete cloud-based ERP suite that connects all applications for seamless access to real-time business intelligence data.
Deepak Wadhwani has over 20 years experience in software/wireless technologies. He has worked with Fortune 500 companies including Intuit, ESRI, Qualcomm, Sprint, Verizon, Vodafone, Nortel, Microsoft and Oracle in over 60 countries. Deepak has worked on Internet marketing projects in San Diego, Los Angeles, Orange Country, Denver, Nashville, Kansas City, New York, San Francisco and Huntsville. Deepak has been a founder of technology Startups for one of the first Cityguides, yellow pages online and web based enterprise solutions. He is an internet marketing and technology expert & co-founder for a San Diego Internet marketing company.