The Digital Factory

Smart Factory XDI

What is a Digital Factory?

Digital Factories are the result of a business/digital transformation strategy to enable the use of data from people, equipment, and systems to identify and prioritize continuous improvement initiatives.

At the heart of the Digital Factory revolution is the management (MOM) layer that makes sense of new found real-time data, pulled from the Levels 0, 1 & 2 and dropped in your IIOT Platform.

There is no single technology that turns an analog factory into a digital factory. However, there are many common technologies and traits that digital factories share, and manufacturers that blend multiple technologies are the ones most likely to be considered:

What are the major technologies of a Smart & Digital Factory?

As you might have read there are somewhere close to nine elements of Industry4.0 for Manufacturing that can provide the technology in a Smart Digital Factory:

The Platform: The Cloud | Interoperability | Cyber Security

These components really are part of the transformation, but really not the starting point.

THE CLOUD: with great production-related undertakings requiring increased data sharing and the cloud’s responsive coming down to milliseconds, it will be the standard across geographies

INTEROPERABILITY: capabilities will become more cohesive vertically and horizontally

CYBER-SECURITY: care “Security by Design” along with ever advancing AI in the security space and increasing threats and exposure, it is a fundamental part of the 4IR

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Cloud and Edge Computing Technology:
Cloud technology empowers digital factories with the ability to store and analyze vast swaths of data using secure equipment they share with others, accessed through the web. Cloud technology affords manufacturers faster and more powerful machines and greater storage capacities (with greater protections) than what is usually feasible to purchase and maintain in-house.

Edge computing takes data coming from the factory floor and processes it close by, removing the wait time it can take to upload to the cloud, analyze, and redistribute info to the factory floor. Edge computing enables real-time analytics and ultra-fast decision-making using data, and is perfect for safety mechanisms, predictive maintenance, and similarly time-sensitive computing tasks.

The Shop Floor / The Field: Cobots | AR | IoT | Digital Twin | Additive Manufacturing

Enter the world of enhanced Field and Shop Floor operations

COBOTS: Yes, amid the drama surrounding robots, the reality is robots and now aptly named Cobots (collaborative robots), will interact with one another and work safely side by side with humans and learn from them.

AUGMENTED REALITY: AR based systems support a variety of services, such as selecting parts in a warehouse and sending repair instruction over mobile devices. As the systems mature, they’ll support workers by providing real-time information to improve decision making & procedures.

IoT: Attached and embedded to components and equipment, these new smart devices will allow field/factory devices to communicate/interact both with one another and with centralized controllers in real-time.

DIGITAL TWIN/SIMULATION: used to model and leverage real-time data, mirroring the physical world care of the digitization of machines, conditions, products and humans.

ADDITIVE MANUFACTURING: while with limited materials today to longer-term potential is exciting for build, maintenance cost and speed

The Intelligence: BIG DATA | ANALYTICS | Machine Learning

In the data economy, the various technologies are there to extract, communicate and use data for enhanced Customer Experiences, Manufacturing and Supply Chain efficiencies.

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Big Data:
In the modern age, data is much, much bigger. This means that traditional methods for acquiring, storing, and analyzing the data are no longer sufficient.

Smart Factories use systems such as Manufacturing Execution Systems to accumulate vast amounts of data in real-time, allowing for quicker, more well-informed decision making.

IIoT: The Industrial Internet of Things connects everything on the shop floor to the internet. This is crucial in creating the “digital twin.” Data is no longer siloed and there is interoperability and increased chances of seamlessexchange of information between enterprise systems such as MES and ERP. With a single source of truth, systems can communicate quicker and more efficiently than with traditional infrastructure.

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Predictive Analytics and Machine Learning:In regards to manufacturing, as well as other industries, machine learning and predictive analytics are one such use case for the collected data mentioned above.

Data can be combined and used to fuel machine learning models that offer decision-making insights from sets of information that can be too complex for humans to derive value from alone.

Machine learning and predictive analytics can be used to forecast demand, perform predictive and prescriptive maintenance on machines, spot openings and opportunities in the market, and much more.

Advanced Robotics/ AI: Smart machines can communicate directly with manufacturing systems while working autonomously with the least human intervention, thereby reducing the chances of variability in output. By evaluating sensory input, these machines are able to solve problems and make decisions independent of people.

Digital manufacturing:Digital manufacturing systems are used to reduce time, cost, and improve the efficiency of production processes. These systems can optimize floor schedules, production planning, material management, and decision making.

Automation:With smart, connected machines comes the opportunity for humans to step aside and allow automation to step in.

In many cases, machines are better able to handle tasks faster and more accurately than their human counterparts.

Industrial automation frees your workforce to focus on other complex/creative tasks that are better suited for human minds than machine minds.

Some digital factories take automation to the next level using lights-out manufacturing techniques that remove humans from the manufacturing process entirely.

“Lights-out”: The ability to start the factory, turn the lights out, and walk out with the understanding that the factory will continue to produce, even 24 hours a day, without human intervention.

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What else do digital factories have in common?

No Paper: Because processes are digitized, there is no need for paper in a digital factory. Everything is stored on the cloud or locally, in digital format.

Connected Stack: As mentioned, it’s less about having one technology or another, and more about having a system of integrated technologies. This can include PLC info from the floor, merged with ERP data, merged with MES and SCADA data, etc. This exchange of information between machines allows for rapid, data driven and machine-led decision making at all levels of the manufacturing process.

Real-Time Metrics:To operate with the type of efficiency expected from a digital factory, manufacturers must have access to real-time metrics that let them adjust on the fly to ensure production goals and other company initiatives are continuing to be met—no surprises.

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How Does a Digital Factory Work?

A digital factory uses advanced technology to automate your manufacturing operations layer and all business practices within your enterprise. Companies undergoing digital transformations have so much to gain.

Using connectivity, a digital factory collects and analyzes real-time data from machine assets. This data is used with your advanced MES/MOM platform for process improvement and automation, developing new maintenance strategies, and providing operators and managers with the necessary insights.

Legacy systems can also be linked to this journey.

This process includes using APIs / Micro Services Widgets to your MOM Platform and other tools to connect legacy software in a two-way, real-time data exchange, including dashboards.

Devices are used to retrofit analog equipment and machines so that data from any generation of equipment and any OEM are included. This comprehensive connection of machine assets, enterprise software, and other critical systems mean that the entire company and all its processes are operating under a single version of the truth.

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Your Step-1: the MES/MOM system

As your organization prepares to morph its facilities into a Digital Factory, it’s important to understand how tools, such as the manufacturing execution system (MES/MOM) software, can help manage these changes.

MES/MOM integrates all databases, machines, and people within your plant(s) into one cohesive, interconnected system that eliminates islands of information, such as handwritten paperwork, whiteboards, Excel spreadsheets, and isolated software systems, while harmonizing your processes across your plants.

MES/MOM technology produces repeatable, precise, and actionable data that is essential for your team to improve plant efficiency, uptime, quality, and overall profitability.

While many plants have very talented people working in them, no one individual can possibly take in all the plant data, analyze it, schedule everything, notify everyone, and point out all the areas for improvement; but MES/MOM tools can.

Through automation, software, and networks, MES/MOM tools can bring all the information and brain power available in a plant into one system.

Here’s a high-level look at four of the most common MES functions and how they help ramp up your digital factory:

OEE & Downtime Tracking

Measures performance, downtime, and product quality to help you understand the “why” and make changes to increase efficiency

Track & Trace

Tracks a batch, work order, or load from raw materials to finished goods for quality, traceability, real-time status, and association of information

Statistical Process Control (SPC)

Digitally tracks the quality standards and acceptable variations of consistency and accuracy, producing better-quality products with less waste

Recipe Management and Tracking

Stores and manages all your recipes to improve recipe versioning, line control, and changeover duration

Other ancillary MES tools may include integration to ERP, scheduling and demand planning, CMMS maintenance management, poka-yoke error proofing, and work instructions and workflows.

What is the future of Smart Manufacturing for the next 10-20 years?

With the increased demand from customers for high-quality products delivered faster at the lowest cost possible, there is an increased requirement to optimize the manufacturing process from raw material to the realization of the final product. This will only increase the need for Smart manufacturing and early steps towards it will ensure market domination in the future. A joint study by the Manufacturer’s Alliance for Productivity and Innovation and Deloitte published in September 2019 found that more than 85% of industrial manufacturers believe that smart factory initiatives will be the main driver of manufacturing competitiveness in the future.

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What are the major barriers for companies to implement Smart Manufacturing?

1. Price

Implementation of Smart Manufacturing techniques is a long term investment at the price tags available. Smart manufacturing is a heavy investment that engineers and manufacturing departments have to convince their business counterparts of the value. Especially given the current times, companies are risk-averse, but they still need to compete and provide a customer-centric experience.

This can lead to Smart Manufacturing and a digital transformation being on a wish list for many, however in the meantime, the disruptors arrive and the existing competitors never stand-still!

Standing-still is going backwards

2. An Undefined Path

Smart manufacturing is a broad topic, and many organizations are unsure of where and how to begin a digital transformation journey. They are hesitant to decide whether to discard or upgrade their existing systems. They are unsure about their commitment to the implementation journey and the scope of the implementation in the future.