Industry 4.0 and Chemical Industry:
The chemical industry faces formidable challenges as a result of the global competitive environment. Right now, the chemical production business is undergoing a major transformation. The question is no longer whether or not to implement Industry 4.0 connectivity and “smart” manufacturing technologies, but when — and where — to begin. To compete by 2020, advanced implementation of Industry 4.0 will be required. It is also likely that investors will view it as a requirement for funding. As a result, any companies that have not kept up will struggle to maintain market share and will face higher capital funding costs.The time has come for such a shift: Advanced technologies relevant to the chemicals industry, such as the Internet of Things (IoT), advanced materials, additive manufacturing, advanced analytics, artificial intelligence, and robotics, have collectively reached a level of cost and performance that allows for widespread application. More importantly, these technologies are now advanced enough to integrate with the core conversion and marketing processes of chemical companies, allowing them to digitally transform operations and enable “smart” supply chains and factories, as well as new business models.

Will Industry 4.0 Simplify the Operations of the Chemical Industry?
Industry 4.0 has enabled the chemical industry to use technology more intelligently, saving them time and effort that was previously wasted in production and back-office operations. The digital-first mindset enables them to leverage the benefits of smarter supply chains and redefined business processes to raise the quality of chemicals to new heights.

The advantages of Industry 4.0 for chemical industry operations:
·         Increased Productivity
·         Reduced Risks
·         Efficient Asset Management
·         Improved Process Controls
·         Improved Supply Chain Planning
·         Better Employee Safety Management
·         Smarter Management of Energy and Resources
·         Increased Business Growth and Revenue

Smart Manufacturing: Intelligent Manufacturing and Operation Technology Marrying     to Enhance Productivity.
Also known as “smart factory,” smart manufacturing combines information technology (IT), Also known as “Smart Factory,” the combination of intelligent manufacturing (IT), IoT, advanced analysis and artificial intelligence, with operating technology, like additives, advanced materials, and robots, combines intelligent manufacturing. This process can benefit chemicals companies in several ways:

  1. Predictive asset management: Plant operators can move from reactive to predictive maintenance by combining the constant input of data collected from sensors with smart equipment.
  2. Process management and control: Real-time analytics and automated control actions are examples of Industry 4.0 technologies that link the digital and physical worlds together, allowing for quality control.
  3. Energy management: Soft or virtual software sensors are examples of Industry 4.0 technology that can help enhance energy efficiency.
  4. Safety management: Companies can use connected technologies to monitor products, byproducts, and waste created in real time, lowering manufacturing risks.
  5. Production simulation: Plant operators can train staff, be prepared before plant operations begin, and benefit from prognostics by utilizing technologies such as 3D visualization and virtual reality.

Supply Chain Planning: Predicting Changes to Reduce Operational Risk.

Industry 4.0 helps chemicals companies plan their supply chains in two ways:

Supply chain visibility: Chemical companies can better manage their supply chain planning by monitoring chemicals in transit. Furthermore, multiple players in the supply chain — from transportation operators to technology providers — might collaborate to achieve a similar business goal.

Demand forecasting: Capacity optimization in the chemical industry can be accomplished through demand forecasting and responsive scheduling. They can identify demand indicators and expand or contract their production capacities as a result.

Research and Development: Developing New Products to Increase Revenue
R&D is perhaps the most important stage in the value chain because it influences not only how products are manufactured but also informs subsequent improvements. Because R&D necessitates significant investment, chemical companies are turning to big data and other tools to forecast the outcome of an investment. In the field of material genomics, for example, advanced analytics assists researchers in understanding the chemical properties of existing materials and considering possible combinations in order to develop new materials with desired properties for specific customers. Technologies relevant to this transformation include:
Additive manufacturing for product testing or development
Advanced analytics for material selection 
4D printing for advanced material development

Smart Products and Services: Making Products Smarter and Developing New Data Services.
Advanced technologies such as the Internet of Things (IoT) may enable chemical companies to add intelligence to their existing products and provide better customer service. Furthermore, chemical companies could supplement their traditional pay-by-the-ton revenue model by providing value-added data services. Chemical companies can deliver value propositions and even build new business models by forward-integrating into their customers’ operations. Products and services in this transformation include:

  • Product recommendations for chemical applications 
  • Data services to supplement existing revenues 
  • New revenue models through forward integrating into customers’ activities

Industry 4.0 Challenges:

When making smart investments in the factory of the future, keep an eye out for these potential hurdles:

a. A Deficit in Technical Skills: The workforce’s requirements are always changing. Is it possible for your employees to keep up? When hiring for unfilled roles, seek for candidates that have “digital dexterity,” meaning they are familiar with both industrial processes and the digital technologies that support them. Business models will only be able to successfully deploy new technology and manage operations if they have the suitable employees.

b. Data Sensitivity: As technology advances, so do concerns about data and intellectual property privacy, ownership, and management. What is a common example? Data is required to train and test an AI algorithm in order for it to be successfully implemented. The data must be shared for this to happen. Many businesses, however, are hesitant to share their data with third-party solution developers. Furthermore, our current data governance policies for intra-organizational use are insufficient to support cross-organizational data sharing. Data is a valuable asset that must be safeguarded.

c. Interoperability: A major issue is the lack of separation between protocols, components, products, and systems. Unfortunately, interoperability limits businesses’ ability to innovate. Furthermore, because they cannot easily “swap out” one vendor for another or one component of the system for another, interoperability limits options for upgrading system components.

d. Security: Another major concern is the threat of current and emerging vulnerabilities in the factory. The physical and digital systems that comprise smart factories enable real-time interoperability; however, this comes at the expense of an expanded attack surface. When numerous machines and devices in a smart factory are connected to a single or multiple networks, vulnerabilities in any of those pieces of equipment could make the system vulnerable to attack. Companies must anticipate both enterprise system vulnerabilities and machine level operational vulnerabilities in order to combat this issue. Companies aren’t fully prepared to deal with these security threats, with many relying on their technology and solution providers to identify flaws.

e. Handling Data Growth: As more businesses rely on artificial intelligence (AI), they will be confronted with more data that is being generated at a faster rate and presented in multiple formats. AI algorithms must be easier to understand in order to wade through these massive amounts of data. Furthermore, these algorithms must be capable of combining data of various types and time frames.

Industry 4.0 Opportunities:

Enough with the challenges; let’s look at some of the advantages that come as a result of Industry 4.0. In the following ways, the new industrial revolution will assist businesses in becoming smarter and more efficient:

  • Optimization and automation lead to enhanced productivity
  • Real-time data for real-time supply chains in a real-time economy
  • Advanced maintenance and monitoring possibilities will enable greater business continuity
  • Real-time monitoring, IoT-enabled quality improvement and cobots (collaborative robots) will lead to higher quality products
  • Superior sustainability and better working conditions
  • Earn the trust and loyalty the modern consumer with personalization opportunities

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