The industrial internet of things (IIoT), the connected factory, is being implemented across many different manufacturing sectors, from healthcare, aerospace to transportation and energy, just to name a few. Over the past five years, IIoT and AI-based technologies have become an absolute necessity for the success and competitiveness of such companies.
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.
Currently, far too many composite component manufacturers are flying blind. Their core systems do almost nothing to support the unique needs of composite part manufacturing. Most cannot even answer the simplest question of all – ‘where is my stuff?’ at any given moment. This means that the management process of valuable composite materials and parts is being done almost entirely manually, resulting in a significant amount of labor and potential rework & material waste.
In fact, the majority of composite component manufacturers lack real-time visibility across their production floors. Production Floor staff and supervisors are not always aware of problems as they occur, let alone are they able to predict them. . The result is production delays, causing longer manufacturing cycles, as plant managers must physically walk the shop floor to discover problems well after there is anything that can be done to prevent them.
Furthermore, the ever-present possibility of an audit means that manufacturers must be able to show the digital thread (‘pedigree’) of every component. Currently, this is often done manually based on paper-trails. However, the implementation of the Digital Thread allows an automated record of every step of the manufacturing process, giving complete traceability from raw material to end product.
We hear all the time that the waste is estimated at hundreds and even up to millions of dollars per year for a mid-size fabricator.
The question manufacturers working with composite materials need to be asking themselves is, ‘how effective are my current digital solutions?’
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For example, ERP systems gather information and manage data-flows; however, they leave it up to the user to figure it out and make decisions. These decisions are inherently limited by the lack of time, data or our human ability to comprehend vast amounts of data.
At Plataine we see the same issues time and time again – composite part manufacturers are tracking material shelf life entirely manually, keeping manual records to allow traceability in case of an audit. Inevitably, lacking any digitization, there is no means to apply the required analytics to make sense of it, optimize the process or enable the required operational flexibility. This is true even where customers are using the most advanced ERP offerings on the market since it is not designed to cope with these industry-specific manufacturing issues.
To learn more about how to choose the right IoT Vendor for your factory, read this guide.
There are two key steps to consider when implementing Digital Transformation in composites manufacturing:
- Step 1:Regain control and visibility.
- Step 2:Make context-aware, data-driven optimized decisions in real-time
Step 1: Regain control and visibility
Throughout the production process, assets inherit information from ‘parent’ assets; assemblies inherit data from kits; and kits inherit data from materials. In addition, tracking of tools and stations for total control and visibility results in a gigantic collection of data points over time. Being able to only access this data is of limited benefit. Analytical capabilities and AI algorithms are also required to analyze the data and provide smart insights and recommendations. The result is real-time, accurate information as kits and rolls go in and out of the freezer providing greater control and visibility.
Mobility platforms (such as tablets and smartphones) and wearable devices replace paper forms, barcode scanners and enable real-time reporting, collaboration, and immediate actions.
Step 2: Make context-aware, data-driven optimized decisions in real-time
To make the IIoT useful, one must leverage the data into analytics and optimized decision making. While current practices rely on serial decision making by separate teams using loosely integrated systems, the IIoT brings the opportunity to practice a holistic approach on the production floor. A fully integrated Total Production Optimization system bridges the gap between engineering and manufacturing, together with complete material and asset tracking on the production floor, to create a true, real-time holistic optimized decision framework. Automated Digital Assistants can then take this information and use it to send automated alerts helping production staff take better decisions on the fly.
Context aware decisions can be made following a holistic approach. AI-based Algorithms are the brain behind ‘Material Smart Selection’: which material to use based on expiration date, ETL (Exposure Time Left) or size. In addition, work orders are triggered based on availability of tools, and the creation of optimized cut plans is made based on data, while taking into account actual availability on the production floor and tool maintenance plans. Fast and optimized adaptation of cut-plans is done in real-time in cases of unexpected changes on the production floor.
COVID-19 is only accelerating a pre-existing trend for manufacturers to adopt digitalization. Although the pandemic has caused many businesses to accelerate their automation plans mainly for the short-term benefits (e.g. being able to run socially distanced factories with fewer staff); the impacts will be much further reaching. That is because, once the market-leading manufacturers have adopted IIoT, the efficiency improvements are such that they will never go back.
