CHEMICAL

Chemical Industry Productivity Challenges

How Chemical companies overcome productivity challenges

How Chemical companies overcome productivity challenges 700 500 Xcelpros Team

At a Glance

  • Agility is a synonym for growth in today’s business environment, and chemical companies are continually attempting to be agile in processes, operations, and outcome to keep up with the changing times.
  • Conventionally, many chemical companies have adopted the reactive model, which is now adversely affecting their overall productivity and market responsiveness.
  • Adapting newer technologies to leverage the maximum out of the infrastructure and fortifying their IT network is essential for chemical companies to improve their output.

Today, the chemical sector has entered a phase of adoption: adapting newer technologies, transformative business models, and more. These changing times create excitement and uncertainty amongst the chemical companies who are continually looking to enhance their market share by driving productivity. While many chemical companies have invested heavily in better, newer IT infrastructure, they have not succeeded in leveraging this infrastructure to its maximum potential. On the other hand, other companies are still wary of going the digital way, creating uncertainty among decision-makers in chemical companies.

According to PWC’s 23rd Annual Global CEO Survey, 33% of chemicals CEOs are not very confident about their company’s prospects for revenue growth in the next 12 months.

It is evident that chemical companies are facing challenges when it comes to improving productivity and growth rate. By looking at how chemical companies can overcome these uncertainties, one would first need to comb through the chemical industry pain points when it comes to driving productivity.

The Chemical Industry Challenges in Improving Productivity:

1.The Steep Fall in Oil Prices:Commodities prices are the catalysts in deciding the outcome rates of the chemical companies. The year 2020 saw an unprecedented decrease in oil prices, causing chemical companies across the USA and the globe to suffer low productivity rates. The soft commodities prices have also caused a massive imbalance in the raw material’s demand patterns, resulting in a disrupted product lifecycle for many chemical companies. Outcomes are getting hit across the board due to affected oil prices.

2.Difficulties in Adapting to Newer Technologies:Adapting newer technologies and tools is not only a smart move but an inevitable one for the chemical companies. The need of the hour to build a robust IT infrastructure can generate and analyze data, automate operations, and streamline the supply chain. However, many chemical companies are still not at an advanced stage of going digital and cannot make use of the latest technologies. Lack of skilled, knowledgeable professionals and consultants also leads to often misguided judgments, causing productivity to take a hit.

3.Lack of Real-time Visibility to Different Stakeholders:Chemical companies involve multiple stakeholders, many of whom are geographically separated. The production process involves changes, call-backs, and unexpected challenges at any point in the chemical product’s lifecycle. However, with legacy systems and reliance on manual intervention, there is a lack of transparency and complete visibility to all the stakeholders involved – leading to process delays, communication gaps, and operational glitches. All these negatively impact the rate of productivity.

4.The Snowball Effect of Covid-19 Pandemic: The COVID-19 pandemic has challenged the business outlooks for the year 2020 in the first quarter itself. Borders had to be closed, transportation had to halt, travel stopped, and plants shut. Supply chains globally were disrupted; operations across chemical plants either slowed down or stopped. The slowdown had a massive effect on the productivity in the chemical sector. Even as the world is slowly starting to open up again, there are still skeletal workforce issues, lack of investments, and demand discrepancies that will continue to haunt the chemical companies.

Figure 1:How Modern ERP Systems Enable Better Productivity

How Modern ERP Systems Enable Better Productivity

The Way Ahead: Overcoming the Chemical Industry Challenges with Digitization

The chemical companies need to embrace technology to keep up with the changing times. Opting for data analytics and automation will streamline challenges in operations management and help maneuver efforts to increase productivity. A healthy IT infrastructure with robust enterprise resource planning (ERP) and management capabilities such as the Microsoft Dynamics 365 Finance and Operations can serve as the one-stop solution for various chemical company challenges.

Figure 2:ERP in Chemical Industry: The Benefits

ERP in Chemical Industry: The Benefits

Microsoft Dynamics 365 ERP helps in keeping track of the budget, managing changing prices and adjusting actuals accordingly, collating and analyzing data from chemical plants and top floor, and many such enterprise management functions. Your chemical company will have a systematic tool that keeps track of orders, bill of material, production processes, supply chain, booking, and revenue that helps immensely in anticipating plausible glitches and avoiding them with proactive measures.

There is no doubt that chemical companies will thrive with the adoption and utilization of technology in its prime. The decision-makers in these companies can bring transformation and enhance productivity by investing in the future and making the right choices of welcoming the change.

Key Takeaways:

  • Changing times call for change in attitude, and the chemical companies will need to integrate this change in every facet of product development to be effectively market-responsive
  • With a robust ERP system and other cutting-edge technologies, the chemical companies can plan and act upon increasing their outcome rate.

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AI ml in chemical industry

Transforming Business with AI and ML in the Chemical Industry

Transforming Business with AI and ML in the Chemical Industry 700 500 Xcelpros Team

At a Glance

  • Innovation is the name of the game for chemical companies to optimize operations and enhance profits. To fast-track innovations, use of AI and Machine Learning in the chemical industry is crucial.
  • Many in the chemical industry are touting benefits of leveraging AI and machine learning to analyze data, systemize processes and mitigate errors by minimizing manual interventions.
  • Human-machine combination is proving to be a transformational phenomenon that can change the way the chemical industry is functioning in the USA and all over the world.

Introduction

The world is growing and seeing changes at an unprecedented rate. The year 2020 has shown us that advancement in science, especially the field of chemicals (and related fields such as biotechnology that deal with the vast majority of chemicals), cannot come fast enough! We need faster, error-free methods to test chemical molecules, computer-generated models for process optimizations, and digitally-adept sensors for quality controls. AI and machine learning play an integral role in efficiently taking the chemical industry towards a trend of modernization and innovation.

The path to digital transformation involves infusing AI into crucial processes and milestones. The journey includes digitizing assets, automating processes based on those assets (known as digitalization), and then creating new ways of doing business.

Figure 1 AI is the greatest commercial opportunity in today’s economy

AI is the greatest commercial opportunity in todays economy

When organizations invest in AI, the goal is to create and enhance digital experiences. AI apps can employ skills to mimic human cognitive functions such as vision, speech, and natural language understanding. By including these human-like capabilities, AI can enable organizations to construct digital experiences that are smart, fast, and helpful to end-users.

A recent study by Accenture shows some promising figures when it comes to use of artificial Intelligence in the chemical industry. According to research, companies that have implemented Industrial AI in the chemical sector are exhibiting significant benefits as follows:

72%report a minimum 2x improvement in some process KPIs

37%report a 5x improvement in KPIs

4 Ways of Applying AI and Machine Learning in the Chemical Industry

While every enterprise has its blueprint to follow when it comes to the application of tools and techniques on AI and Machine Learning, certain broader areas can be common for the chemical industry. Let us have a look at 4 such facets:

01.Data Crunching and Analysis for Molecular Activity Studies

Understanding chemical products and utilizing them for desired effects usually take years of analytical studies, laboratory experiments, clinical trials, farm trials, etc. However, these days, faster results that can mitigate manual errors and minimize efforts are required. Machine learning and AI tools are effectively used to feed and churn a humongous amount of data, and can systematically analyze the said data. This data churning and analysis will help separate chemicals that are effective yet have fewer or no side-effects from the ones that do not have desired effects or are toxic. Apart from the use of AI and machine learning in the pharmaceutical and pesticide industry, possibilities can also be explored in the manufacturing industry, which is heavily dependent on chemicals. Applying AI and machine learning in the chemical industry can also help expedite the efforts in fighting climate change by estimating the damage done by harmful pollutants. This will aid companies in making essential changes in their machinery and processes to minimize the pollutants being released into the water bodies and air.

02.Result-oriented Innovation and Boost in the Chemical Industry R&D Sector

R&D forms the backbone of any industry, and the chemical industry is no exception to this. Today, major players in this sector are looking for focused R&D and innovation that can yield faster and more accurate results following the use of artificial intelligence in the chemical industry. Machine learning tools can help in exercising this type of quick research with the help of computerized permutations and combinations. It can also help in recognizing the right molecules, generate formulas, and aid in knowing the precise quantities of different chemicals required. AI, on the other hand, can help in predicting chemical combinations that can be a breakthrough in terms of innovation. These innovations can boost the ongoing and upcoming efforts in the pharmaceutical, food, biotechnology, oil and gas, petrochemical, manufacturing, and many such industries.

03.Seamless Juxtaposition of Human and Machine Efforts

Since the introduction of computers in the workplace, humans and machines have proven to be the best combination for effective results. However, digital transformation and the introduction of layers and layers of machine-generated intelligence can make this combination even more successful than ever before. Imagine an idea that has come out of the human mind, but it can be analyzed, tested, and streamlined to mitigate risks or errors even before it has physically been put to the test? This can lead to unprecedented time and efforts being saved. Such amalgamation of human and machine efforts can influence the chemical industry to fast-paced innovations, productions, operations optimization, and other concurrent developments.

04.Preventative Measures and Predictive Forecasting

In today’s industrial world, competition is steep and it is essential for enterprises in the chemical industry to be prepared and to be proactive. AI and machine learning tools can help a great deal in this by predicting snafus or future maintenance requirements. Advanced analogs and mathematical models can also be used to estimate oil, gas, and other raw material demands so that the companies can streamline their supply chain in a manner that avoids potential delays and last-minute cost hikes.

While these applications of AI and machine learning cover the broad spectrum when it comes to the chemical industry, there is still a lot of research and development going on in this field. As the world embarks upon a new journey of Industry 4.0, it would be interesting to see more transformations brought in by the use of artificial intelligence in the chemical industry.

Where is the Challenge?

AI-enabled systems are helping companies achieve objectives, goals, and enhance user experience. However, each time a system is not maintained correctly, the process begins to decay by behaving unpredictably. Organizational leadership can thus lose confidence in AI as a process enhancement system. Moreover, organizations should have the required maturity—which encompasses strategy, culture, organizational structure, and core capabilities—to own an AI-based system responsibly. In some cases, this may mean a withdrawal or rejection of AI technologies based on unsuccessful attempts to adopt AI. Organizations or their customers may lose trust in AI as a technology, branding it as unpredictable or too hard to operate. This outcome will push real digital transformation further away and cause the organization to miss out on the powerful impact that AI can have on their business.

Microsoft has worked on defining an operational model that helps organizations assess their attributes that contribute to the adoption of AI technologies. A well designed AI Maturity Model assists organizations in gathering information related to the core characteristics required for teams. Forward-thinking organizations that have embraced AI are witnessing improvement in user behavior. The transformation meets all prime objectives of a Chemical company, mainly driving productivity, sales, Environment Health and Safety, appropriate management of hazardous chemicals in the warehouse.

Figure 2AI Maturity Model

AI Maturity Model

Additionally, Microsoft has compiled prescriptive guidance associated with adopting the right AI technologies for an organization’s current maturity level, while advising on how to increase maturity to embrace more advanced AI capabilities.

Key Takeaways

  • AI and machine learning in the chemical industry can be critical players in clinical trials, farm trials and overall study of chemical molecules.
  • With the cutting-edge application of AI and machine learning tools, the chemical industry can streamline its processes and supply chain for better operations and enhanced profitability.

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Chemical Industry Software Solutions

Active Ingredient Management in Microsoft Dynamics 365

Active Ingredient Management in Microsoft Dynamics 365 700 500 Xcelpros Team

At a Glance

  • Active Ingredient Management and Potency-Based Pricing are highly relevant to process manufacturing, distribution, and other manufacturing industries.
  • The products in these industries consist of Active Ingredients, Compensating & Filler Ingredients (sometimes referred to as buffers, fillers and excipients).
  • Active Ingredients and Potency have a significant impact on price variations in-turn affecting downstream functions such as customer billing and value.
  • In order to calculate potency, it would be required to maintain min, max and target values of batch attributes such as potency, concentration and purity on items, inventory or batches.
  • The calculation of a potency-based price that is dependent on the percentage of active ingredient purity or potency can be achieved by maintaining an attribute-based price with algebraic equations.
  • The industry requires that the purity and potency of active ingredients be captured at the time of incoming inspection / receipt of the product or at the time of quality testing of goods received.
  • Batch attributes, such as potency and purity, captured at various stages of the operation have an impact on the value of physical and financial inventory.
  • Unit of measure conversion from weight or volume would be a key element in determining the appropriate price for a certain customer-specific batch and potency requirement.
  • Manufacturing an item with a specific active ingredient, requires an ability to maintain a specific weight or volume-based formula and be able to balance a batch using compensating and filler ingredients with a compensating factor.

Which industries is this relevant to?

  • Chemicals (Specialty, Bulk and Distribution)
  • Pharmaceutical (Manufacturers & Distributors)
  • Food & Beverage
  • Cannabis
  • Distribution
  • Textile and
  • Paper

Active Ingredient Tracking

Highly regulated and process industries such as Chemical, Pharmaceutical or Food & Beverage have an inherent operational need to manage and account for active ingredients.

Batch attributes such as potency and purity are maintained in the system along with pricing based on target values. Behind the scenes, an algebraic equation combines the unit price, quantity, batch attribute – target & actual values and determines an automatically adjusted price within the target transaction such as purchase order or sales order invoice. A key element for active ingredient management is to be able to capture potency, purity or other batch attributes during quality testing of a batch. This allows you to view inventory by recorded batch attributes and reserve these batches for the appropriate transactions. As stated above, leveraging the pricing formula allows you to implement price adjustments to the downstream transactions based on actual values.

Microsoft Dynamics 365 for Finance & Operations has extensive out-of-the-box functionality to help manage active ingredients for both make and buy items.

Item Batch Attributes

Batch Attributes are properties of raw materials, intermediates or finished products that capture the key distinguishing factors for an inventory batch. These attributes vary by industry, use and other factors such as environmental.

As discussed above, in Microsoft Dynamics 365, you have the ability to manage item batch attributes such as potency and purity. The first step would be to create an item that is tracked at a batch level and define batch attributes that can handle a range of potency values. Dynamics 365 allows for managing multiple attributes for the same item, including one primary and multiple secondary batch attributes.

A few examples of batch attributes in different industries:

Industry Example of Batch Attributes
Chemical & Pharmaceutical Potency, Purity, Concentration etc.
Food & Beverage Fat Content, Percentage Weight, Moisture, Age
Steel / Metals / Mining % of Magnesium content
% of silver content
% of zinc content
Cannabis % of CBD
% of THC
Purity
Contamination etc.

The screens below provide a quick view of what batch attributes look like in Dynamics 365 for Finance and Operations.

Figure 1 Released products – Caustic Soda

Released products - Caustic Soda

Figure 2 Released Product Details – Product Tab Expanded

Released Product Details - Product Tab Expanded

Figure 3 Released Products – Manage Inventory Tab Expanded

Released Products - Manage Inventory Tab Expanded

The screens below show product-specific batch attributes that can be set for either purity or potency with an acceptable range and a target value.

Figure 4 Released Products Attributes – Purity

Released Products Attributes - Purity

Figure 5 Released Products Attributes – Potency

Released Products Attributes - Potency

Purchasing and Receiving Items with Active Ingredients: Attribute-Based Pricing

There are times you may purchase one or more items from an approved supplier with a specific active ingredient and it may be required to track active ingredients’ potency at a specific value.

To learn more about the receiving process in Microsoft Dynamics 365, refer to “An Overview of Chemical Distribution in Microsoft Dynamics 365”

When an item has batch attributes, you receive the item batch and enter the batch attribute value along with the vendor batch details. The attribute-based pricing that is derived during invoicing alters the unit price and net amounts based on the potency value of the batch.

Purchase prices for active ingredient purity or potency can be maintained in the attribute-based pricing details section shown in the screen below.

Figure 6 Attribute-based pricing details

Attribute-based pricing details

Figure 7 Attribute-based pricing for Caustic Soda based on Pricing Formulas

Attribute-based pricing for Caustic Soda based on Pricing Formulas

Figure 8 Purchase Orders – Purchase Order Lines

Purchase Orders - Purchase Order Lines

The screens below show the different batches in inventory with specific batch attributes.

Figure 9 Batch Tracking (These are the batches in inventory with specific batch attributes. You can add / remove columns you want to see in any view)

Batch Tracking

Figure 10 Released Products – Inventory Batch Attributes

Released Products - Inventory Batch Attributes

Manufacturing with Active Ingredients

Caustic Soda is just one example to demonstrate active ingredient management in process industries. The same concepts can be applied to different types of chemicals or products that contain a variety of batch attribute requirements.

A formula is defined by taking active ingredients, compensating & filler ingredients and applying a conversion factor to calculate the totals on batch production. Microsoft Dynamics 365 is able to meet this requirement with the included batch balancing functionality.

Manufacturing to meet a certain potency by using active ingredients can be tricky if you do not have a way to calculate amounts based on the potency of the active ingredient batch picked during production. When a formula is setup to meet a specific potency requirement, the weight / volume of the active ingredient, compensating ingredient and filler ingredients need to be defined.

Figure 11 Released Products – Inventory Batch Attributes

Released Products - Inventory Batch Attributes

Figure 12 Released Products – Formulas Details

Released Products - Formulas Details

Formulas can be setup by maintaining the quantities of Active, Compensating and Filler ingredients along with a compensating factor designed to automatically adjust batches.

With a compensating factor, the system will recalculate and adjust batches as needed to produce desired potency values. The compensating factor always refers back to the base value, in order to correctly calculate batch quantities.

Figure 13 Formula Lines – Compensating Principle

Formula Lines - Compensating Principle

Figure 14 Compensation Principle Example

Compensation Principle Example

Batch orders created for the item in Fig. 14 (shown above) will have standard values proposed at the time of estimation. When the batch order is started and the appropriate active ingredient batch is picked with a specific potency, the batch balancing function in Microsoft Dynamics 365 provides the ability to balance the ingredients based on the compensating principle setup in the Formula.

Figure 15 Production Orders – Batch Order

Production Orders - Batch Order

Figure 16 Production Orders – Batch Balancing – By confirming the formula, the balanced quantity is automatically selected to continue through the process

Production Orders - Batch Balancing

Active Ingredient Attribute-Based Pricing for Customer Billing

Similar to purchasing, potency-based pricing can also be active during the sales process and within customer billing.

Using the same Caustic Soda example as above, if you sell a Caustic Soda tote, the calculation will auto-adjust billing based on the potency or purity selected. I will illustrate the Caustic Soda billing based on the purity of the batch consumed through the example below.

The Caustic Soda tote is created as a product in Microsoft Dynamics 365 with a specific purity of Na2O as the base attribute. This includes an acceptable range of Na2O purity and any other customer-specific requirement for the batch. The illustration of this example starts with assigning a batch attribute and a target value of the attribute. For Caustic Soda, we use batch attribute ‘purity’ of Na2O. Microsoft Dynamics provides the ability to capture multiple attributes for an item, in this case the purity of Na2O which is the active ingredient and the purity of Caustic Soda itself becomes relevant for pricing purposes.

Figure 17 Batch Balancing

Batch Balancing

Figure 18 Released Product Details – Label Print Options

Released Product Details - Label Print Options

Microsoft Dynamics provides the ability to maintain product-specific as well as customer-specific batch attributes. For example, if your customer has additional potency requirements on the batch, over and above purity, the system provides the ability to maintain acceptable potency values for the batches that would be sold.

Figure 19 Released Product Details – Manage Inventory Tab Expanded

Released Product Details - Manage Inventory Tab Expanded

Product information management in the system has the ability to maintain attribute-based pricing from trade agreements, which is a journal to maintain sales and purchase prices.

Figure 20 Compensation Principle Example

Compensation Principle Example

In the example shown in the screen below (Fig. 21), the sales price is maintained in pounds for an effectivity date that is tied to an attribute-based price calculation. This can include an algebraic equation that adjusts the price based on the purity or potency of the batch being sold.

Figure 21 Attribute-based Pricing – Trade Agreement for Sales Price

Attribute-based Pricing - Trade Agreement for Sales Price

The figure below shows the calculation that includes the purity of Na2O and Caustic Soda if the price is dependant on both attributes.

Figure 22 Attribute-based Pricing Details – Trade Agreements

Attribute-based Pricing Details - Trade Agreements

In this example, we demonstrate the use of a simple calculation based on actual purity and target values. The system would read the below calculation and, based on the actual value of the batch, automatically adjust the price on the customer’s bill.

Figure 23 Attribute-based Pricing

Attribute-based Pricing

Figure 24 Attribute-based Pricing

Attribute-based Pricing

The invoiced sales order below shows the adjusted price for the batch based on the purity of Caustic Soda.

Figure 25 Sales Order with an Invoiced Line

Sales Order with an Invoiced Line

Key Takeaways

  • Active Ingredient Management functionality in Microsoft Dynamics 365 distinguishes the “Active” content of the material from the other compensating or filler ingredients.
  • This function ensures that a company gets paid for the active ingredient content it delivers to its customers and pays its vendors only for the active or potent content of the product.
  • Microsoft Dynamics has the ability to proportionately adjust price on downstream transactions based on the quality test results captured on the Batch Attribute which determines the percentage of the Active Ingredient in the product.
  • The system has the ability to track and maintain inventory based on the percentage of the Active Ingredient.
  • Microsoft Dynamics 365 for Finance & Operations delivers powerful and comprehensive out-of-the-box functionality to support Active Ingredient and Potency Management that is critical to the process and other highly regulated industries.

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