The Range of benefits brought from the Web of Things extends across four dimensions:
Traditional manufacturing installations usually present themselves as a collection of loosely-coupled “cogs”, governed by some general rules, often paper-based.
By making those”cogs” smarter, manufacturers can achieve higher levels of automation, eliminate low-value and unnecessary production measures, and make the whole system function as a cohesive whole. Specifically, Internet of Things automation capabilities lead into the next improvements:
Data-backed Performance Measurement and Management
Sensors can monitor, record and transmit information related to all measures of the manufacturing process – from inspection of incoming materials to shipping.
After that, an Internet of Things big data analytics system can combine the internal data with the external one (e.g., provider specifications, market trends, etc.) and deliver a 360-view of the production system performance. The obtained insights can be applied to constant optimization of the manufacturing pipeline and effective resource planning.
Improved Decision-making and Problem-solving
Increased visibility will allow your teams to make weighted decisions about further improvements or changes.
Root-cause issues become easier to locate and even mitigate before the incidence. Predictive analytics tools can warn your personnel well in advance about the potential equipment failures or quality issues. As your system accumulates more data, it will become capable to predict even more complicated difficulties and offers actionable prevention strategies.
Encompassing, real-time data collection and analysis make production systems more responsive to changes. Whenever a bottleneck or a deviation occurs, it is instantly flagged for inspection.
On-the-ground staff can spend less time on manual optimization and system check-ups as all issues will be diagnosed programmatically, accelerating the entire improvement cycle.
IoT enables your employees with instant access to the necessary information and tools at the right time. Your teams get a unified perspective of the production system and can proactively address any issues.
For instance, the analytics interface can present the team leader with current and historical data on a specific procedure, pinpoint the existing problem and suggest relevant root cause problem-solving tools and best practices.
To capture even more benefits of IoT, you can unlock your own body to external issues. Providers can track consumption and quality issues in materials, and perform adjustments at their conclusion; auditors can receive a clear outlook in to your data and ensure that you are compliant; and equipment manufacturers can review, track and control the provided machinery remotely.
Backing up your manufacturing life spans by Big Data Analytics and IoT means that you can not just create new”best practices”, but also ensure that this new way of doing things is simple.
The optimum settings can be just one click away. Your workers ought to see and experience the clear value of the new system, rather than fret about”how things were easier back in the day”.
Smart systems can also increase organization-wide transparency and knowledge flow as all staff receive access to a centralized repository of best practices, ideas and expertise, created by different divisions.
How to Unlock the Power of Industrial IoT in Manufacturing
To align IoT, big data and manufacturing, enterprises should focus on the following four areas:
Data Warehousing and Infrastructure
Your legacy systems may not suffice for the increased variety of data you’ll need to collect and operationalize. IoT-based jobs are typically hosted in the cloud. With on-demand elasticity and pay-per-use pricing, the cloud is a far more attractive candidate for storing Big Data and conducting large-scale analysis.
Think about a strong software framework as well. SAP HANA is a solid choice in this case, as it comes with a host of attractive cloud products and seamless integration with Azure hosting.
Accumulating and processing large quantities of data at a rapid pace gets easy, even if dealing with multiple linked devices.
Advanced Analytics Suit
Based on your needs, you may want to either produce a custom algorithm or leverage predictive capabilities that are now pre-furbished into many industrial IoT platforms such as Microsoft Azure IoT, SAP Predictive Maintenance Software, Amazon AWS IoT, IBM Watson IoT and GE Predix.
Comprehensive Reliability Engineering Analysis
Before you can optimize your procedures, you’ll need to establish the baseline metrics. To assess the potential impact and severity of failures, schedule a merchandise reliability analysis, applying different tests to establish how the devices will function under certain conditions within a certain timeframe.
Businesses with mature IoT systems can forecast issues with equipment, software or service parts months in advance, even before they resurface as a detectable warranty claim.
Lack of qualified workers, capable of operating smart plants, is a pressing sector issue. Talent acquisition and on-site training must become the top priority for organizations planning to undergo the transition. While smart systems bring automation at scale, they still need to be supervised and maintained by experienced staff, or otherwise, their value to the creation will remain low.
The same holds for off-site expertise, responsible for creating the software back-end of your smart operations. Finding experienced partners will be key to ensure rapid and effective transition towards Business 4.0.