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How AI can be used as a “Game Changer” in Manufacturing.

The use of Artificial Intelligence in manufacturing can be a game changer given that even small gains in yields, capacity and utilization can result in significant financial, time and market gain.

Artificial Intelligence (AI) is transforming the manufacturing landscape by enabling smarter, more efficient production processes. This white paper explores the various applications of AI in manufacturing, ranging from predictive maintenance and quality control to robotics and supply chain optimization. It highlights the benefits of AI, including enhanced productivity, improved product quality, and reduced costs, while also addressing the challenges such as data security, high initial investments, and workforce displacement. The insights provided aim to guide industry stakeholders in adopting AI technologies effectively to remain competitive in a rapidly evolving industry.

#ai #higgins #work #manufacturing #yields #capacity #processexcellence

As a special bonus, a white paper on the detailed steps of applying AI in manufacturing can be accessed through this newsletter!

What’s the SOURCE Reasoning for AI Use in Manufacturing

The integration of artificial intelligence (AI) in manufacturing is revolutionizing the industry, enhancing efficiency, improving product quality, and enabling innovation in various ways. Here are some of the key reasons why AI is becoming increasingly essential in manufacturing:

Increased Efficiency and Productivity: AI can automate complex processes and manage repetitive tasks that are time-consuming for humans. This frees up workers to focus on more strategic, value-added activities. AI systems can also optimize production schedules and workflows to maximize output and minimize downtime.

Predictive Maintenance: AI tools can predict equipment failures before they occur by analyzing data from sensors and historical performance records. This proactive approach to maintenance helps prevent unexpected breakdowns, reduces downtime, and extends the lifespan of machinery.

Quality Control: AI enhances quality assurance by providing advanced inspection capabilities through machine vision systems. These systems can detect defects or anomalies with greater accuracy and speed than human inspectors, ensuring that products meet high quality standards.

Supply Chain Optimization: AI algorithms can optimize supply chains by analyzing vast amounts of data to forecast demand, manage inventory, and determine optimal delivery routes. This helps in reducing waste, lowering costs, and improving service delivery.

Customization and Design: AI can assist in the design process by simulating how new products will perform under various conditions, allowing manufacturers to iterate designs quickly and efficiently. Additionally, AI can enable more customized products as it allows for rapid adjustments in production processes to accommodate specific customer requirements.

Worker Safety: By monitoring workplace environments and operational parameters, AI can identify potential safety hazards and alert workers or shut down equipment if necessary. This helps in preventing accidents and ensuring a safer workplace environment.

Energy and Environmental Efficiency: AI can optimize energy use in manufacturing processes, significantly reducing costs and environmental impact. AI systems can manage and adjust power consumption dynamically based on real-time demand and operational conditions.

Data-Driven Decision Making: AI helps in aggregating and analyzing data from various sources across the manufacturing process, providing actionable insights that can lead to informed decision-making. This can include adjustments to production methods, enhancements to product design, or changes to supply chain strategies.

By leveraging AI, manufacturers can achieve greater operational efficiencies, produce higher quality products, and respond more agilely to market demands and changes. This ultimately leads to a more competitive and resilient manufacturing sector.

Read more about this section in The Higgins AI Directive White Paper - Episode 3 that is available for download and printing.

OBSERVATIONS on the Challenges of AI in Manufacturing

In consultation with many large and mid-sized companies, it is clear that the benefits of AI in manufacturing are real and game changing. However there is always the worry of the challenges that can come with AI implementation especially in a manufacturing setting in which every minute of operation is so critical to success.

These are some of the significant challenges, each accompanied by strategies for effective management:

1. High Initial Costs: Mitigate through government grants, partnerships, and phased strategies to spread costs.

2. Data Privacy and Security: Address by implementing advanced cybersecurity, regular audits, and ensuring regulatory compliance.

3. Integration with Existing Systems: Use middleware solutions and incremental upgrades to bridge old and new systems.

4. Workforce Displacement and Resistance: Alleviate fears by emphasizing AI as an aid, not a replacement, and investing in training.

5. Skill Gap: Bridge the gap between current skills and those needed for AI with training and hiring specialists.

6. Reliability and Safety: Ensure through rigorous testing, simulations, and strict safety protocols.

7. Ethical and Legal Considerations: Navigate by staying informed of laws and consulting with experts.

8. Maintenance and Upgrades: Maintain effectiveness with dedicated teams for regular system evaluation and updates.

9. Scalability Issues: Design systems to be modular and adaptable from the start.

10. Dependency and Over-reliance: Mitigate risks by developing hybrid systems that include human oversight and robust backup systems.

In short, this is the summary of Key Strategies:

Conduct risk assessment and management.
Engage stakeholders across all levels.
Foster a culture of innovation.
Build technology partnerships.

By strategically planning and proactively managing these challenges, businesses can effectively implement AI to enhance efficiency and align with broader organizational and ethical standards.

A detailed Higgins AI Directive White Paper can be downloaded and will address many of these topics in the list.

Artificial Intelligence in manufacturing cannot replace all the talent that goes into fabricating a product. It can only energize their skillsets and efficiency to a new level of performance.

The next section and this weekly Newsletter will provide practical, implementable use case examples of how high performing AI can be applied using these security points to validate its use in everyday work life.

LEVERAGING Real Case-Studies AI in Manufacturing

To make this real, we can leverage case studies that demonstrate the application of artificial intelligence (AI) in manufacturing across various industries, highlighting how AI technologies solve specific problems and enhance efficiency.

General Motors (Automotive): Implemented AI-driven robots to handle repetitive tasks, increasing production speeds by 15% and reducing worker injuries by 20%.

Samsung Electronics (Electronics): Used AI to optimize assembly line parameters in real-time, reducing production time by 20% and significantly improving yield rates.

Pfizer (Pharmaceuticals): Integrated AI to continuously adjust environmental conditions, improving production yield by 15% and reducing times by 20%.

Airbus (Aerospace): Deployed AI tools for dynamic inventory management, cutting inventory costs by 25% and improving delivery punctuality.

Zara (Textiles): Utilized AI to analyze trends and optimize production schedules, significantly decreasing unsold inventory and boosting sales.

Coca-Cola (Food and Beverage): Implemented AI to ensure consistent product quality, reducing waste and improving compliance with health standards.

Caterpillar (Heavy Machinery): Applied AI for predictive maintenance, reducing downtime by 30% and maintenance costs by 25%.

Nucor (Steel Industry): Used AI to optimize energy use and production timing, decreasing energy consumption by 10% and increasing efficiency by 15%.

BASF (Chemicals): Leveraged AI to analyze data and optimize chemical reactions, enhancing production rates and cutting energy usage by up to 20%.

Komatsu (Construction): Developed AI-equipped machinery for autonomous tasks like digging, enhancing operational efficiency by 25% and improving safety.

These cases illustrate the transformative impact of AI across different manufacturing sectors, showcasing significant gains in production efficiency, safety, and quality control.

Read more about these use cases in The Higgins AI Directive White Paper - Episode 3 that is available for download and printing.

VALIDATING AI Future in Manufacturing

Emerging technologies like machine learning, IoT, and blockchain are set to significantly enhance AI's role in manufacturing. These technologies will revolutionize aspects like supply chain transparency, predictive analytics, and quality control. The future of AI in manufacturing is characterized by several key trends:

1. Autonomous Robots and Cobots: Their use is expected to grow, performing tasks alongside humans to enhance productivity and safety. This will lead to more adaptable and flexible production lines.

2. Predictive Maintenance: Becoming more sophisticated, this uses machine learning to predict equipment failures before they occur, thereby minimizing downtime and extending machinery life.

3. Digital Twins: Virtual replicas of physical devices allow manufacturers to simulate and optimize designs and processes before actual implementation, significantly reducing development time and costs.

4. Integrated AI Across Supply Chains: AI is being integrated across supply chains to improve visibility, optimize logistics, and enhance supply and demand management, resulting in more resilient supply chains and reduced costs.

5. AI-Enhanced Quality Control: AI is automating inspection processes and enhancing defect detection, leading to higher product quality, lower defect rates, and increased trust

These trends indicate that as AI technologies evolve, their integration will transform the manufacturing industry, making it more efficient, cost-effective, and adaptable to changing market conditions. Manufacturers that leverage these AI advancements can expect substantial gains in productivity, quality, and operational agility, securing a competitive edge in a rapidly evolving industrial landscape.

For more details, click to download the The Higgins AI Directive White Paper - Episode 3 that is available for download and printing.

Click to Get White Paper

This is only quick snapshots of what AI can do. Subscribe and get weekly to gain insights and examples of how AI can ‘securely’ change your everyday for the better !

Subscribe and get periodic insights and examples of how AI can ‘securely’ change your everyday for the better !

EMPOWERING To Take Action!

Want to get a free personalized proposal on how AI can be efficiently, safely and securely applied to benefit you? Schedule a value-add 30 minute consultation to see how AI can specifically impact you and your work!

Just 30 minutes can start you on the path to effectively integrate AI into your business.

This is an opportunity to leave with a confidential personalized plan and your own free Higgins AI demo so you can proceed to effectively integrate any AI into your everyday. It's our way of appreciating your valuable 30 minutes.

We care so much about your time. To that end, this is what you will get from the session:

Personalized free detailed AI integration proposal.
Tools and insights on how you can unlock some of the solutions to the problems that you are facing today at home, work or life.
Introduction to simple systems that have been proven over decades to quickly improve how you tackle your top-of-mind challenges and more importantly, how feel about them.
Free Higgins AI App Standard demo with your data.

All it takes is one step to begin the process of quickly, safely and securely integrate AI into your everyday. Schedule some time with us today.

We are looking forward to hearing from you!

What is the S.O.L.V.E. Method?

The S.O.L.V.E. Method is a proprietary five-step process designed to accelerate the transition from identifying problems to implementing solutions within a company, often at a cost comparable to that of traditional proposals. This method has been proven through numerous successful implementations, leading to significant improvements and substantial return on investment. Below is a summary of each step along with their impact:

Step 1: SOURCE the Challenge

Identifying the true source of a persistent company challenge is crucial. Often, these sources are not obvious and may relate to deeply ingrained, "invisible" issues that cause repeated failures of attempted solutions. This step involves using specialized tools and certified solution agents to deeply understand and unmask the root causes of problems.

Step 2: OBSERVE Company Experts and Working Style

Traditional methods like surveys or interviews can miss context crucial for fully understanding challenges. By directly observing how experts work within their environments, this method uncovers additional challenges, significantly increasing the effectiveness of the solutions proposed.

Step 3: LEVERAGE Existing and Past Company Solutions

Often, the necessary solutions have already been identified by company experts but failed during implementation due to various oversights. This step revisits these solutions, aiming for a win-win outcome by ensuring all key stakeholders see the benefit, supported by a cross-functional team of Solution Agents.

Step 4: VALIDATE the Solution with a Minimal Viable Pilot

Before full-scale implementation, a minimal viable pilot is conducted to test the solution in a smaller segment of the company. This approach helps to de-risk the solution, adjust as necessary, and demonstrate early benefits to gain wider organizational support.

Step 5: EMPOWER Teams to Champion the Solution for Sustainability

The final step involves scaling the solution and training teams to manage the new processes. The goal is to make the solution sustainable without ongoing external support, allowing continuous improvement from within the organization.

Impact and AI Integration

Implementing the S.O.L.V.E. Method has led to over 355% ROI across various projects, amounting to significant cost avoidance and enhanced operational efficiency. By coupling this method with AI, companies can further sustain and enhance the gains achieved. AI tools can ensure standardized application of new processes and continuous improvement, maintaining the benefits long-term.

In summary, for businesses considering strategic changes, the S.O.L.V.E. Method offers a structured approach to tackling longstanding issues with innovative solutions that are both effective and sustainable. Stakeholders are encouraged to consider this method not only to solve current problems but to transform challenges into opportunities for growth and improvement. The integration of AI can further leverage this method by ensuring consistency and fostering an environment of continual enhancement and adaptation.

You can read more about how S.O.L.V.E. is used at https://malik.partners/mp-research-index

How to make AI secure for any sized enterprise.

AI can be very powerful yet without the right controls in place, it can detract staff away from their jobs rather than enhance their performance. The key is to ensure information from the AI is securely provided to the correct associate that has the necessary permissions to review the answers from the AI.

This article will address some of these security concerns and how AI can be implemented to add value in a secure and compliant manner.

As a special bonus, a white paper on the detailed steps of how to apply AI security can be accessed through this newsletter!

What are Sources of the risks in using AI

In contact with inner management circles, there is a growing anxiety with AI as more leaders are getting worried that this technology, which is estimated by the Bank of America to $15.7 trillion by 2030 (BofA Reference Article), is passing them by. Yet, many still remain on the sidelines, as they grapple with the potential risks associated with letting AI disseminate information to their organization with little or no control.

In fact, Mckinsey recently conducted a flash survey of more than 100 organizations and found that “63 percent of respondents characterize the implementation of gen AI as a “high” or “very high” priority. Yet 91 percent of these respondents don’t feel “very prepared” to do so in a responsible manner” (McKinsey Reference Article). This is indicative of many companies that we regularly converse with. The executives are wary of unleashing AI without controls and for good reason.

These are just some of the risks involved with implementing AI:

AI will divulge sensitive corporate information.

It’s a real concern. If not properly controlled with limited access to applications, data lakes and databases, unvetted data can eventually make it to the AI and be distributed without anyone knowing it. This poses a great risk, especially around trade secrets.

Unauthorized personnel will get access to data.

Even if the data is controlled, it is still possible for associates to be given access to information that was not intended simply because the AI had access to it. This can happen without the associate or those in charge realizing that this information is being disseminated.

Associates can be misled by uncontrolled AI responses.

If AI is let loose without any controls, the chance that “false narratives” can enter company discourse is high. A recent paper published in AI and Ethics stated that there may be “significant cyber security threats generative AI models pose, including potential ‘backdoors’ in AI models that could compromise user data or the risk of ‘poisoned’ AI models producing false results” (AI and Ethics Reference Article). That’s why it’s so important to ensure there are controls AND security in place when implementing AI. The ways that can be accomplished will be discussed later in this article.

AI will require new IT security infrastructure-structure and drain many resources.

There is a common perception that these complex AI systems require critical security infra-structure to be built, specific expertise hired and modifications to existing systems required in order for AI to be benefit. This belief cements the thinking that AI drains resources, time and money that could be used to just get the job done in the traditional manner.

AI learnings and data can leak outside the private corporate network.

Above all, many associates and even their leaders are “quietly” concerned that even the perception of AI implemented in their department could result in layoffs as executives work to trim costs to increase company profitability. This stark outcome hangs on the heads of many leaders I speak with as they try to balance their team’s workload while not being left behind by the advancing AI technology.

There are many more security concerns that need to be addressed with AI. The list above is by no means inclusive of all of them. What’s even more profound than the risks are the way there are perceived in the business community. The next section will address that.

Observations on the Security of AI

In consultation with many large and mid-sized companies, it is clear that security is on their minds when they think of AI. There is always the worry that AI will go wild and uncontrolled interaction with their staff will result in chaos in the workplace. Some professionals I spoke to stated, and I paraphrase:

“What if the AI responds in an inappropriate way?”

“How can we control the narrative of the AI to ensure it defines company terms the way we want it to?”

“What if the use of our private and restricted AI encourage associates to use the unrestricted public once’s to get more functionality?”

“How can we limit the AI about mis-informing our associates on regulations that then puts the company at a compliance risk?”

“AI records question-answer conversations that pose a security risk depending on who has access to them.”

The trouble is that the concerns above are valid and without a secure, controlled AI, a company could be facing one or more of the risks mentioned. The next section and white paper attached goes into some steps that can be used to make AI implementation safer for an enterprise.

Leveraging High Performing AI in a Secure Manner

The common misconception that we often hear, that a company controlled, restricted AI is less performing than the open public ones is not always the case. In fact, if designed and implemented properly, the AI can unleash incredible productivity as outlined in our previous newsletter (Higgins Newsletter Article 1).

Fortunately there are lots of non-technical AI security material like the one produced by the NCSC that provides guidance on how to safely proceed with AI (NCSC Reference Article).

We will highlight what we believe to be some of the key points to address to balance AI security with performance. Some are obvious while others are less intuitive than our clients expect:

Review AI Security Risks Reduction Strategies
Implement Machine Learning Security Measures
Secure Model Training Practices
Audit and Monitor Machine Learning Models
Design and Implement Cybersecurity Strategy for AI Systems
Ensure Privacy Protection in AI
Utilize Privacy-Preserving Technologies for AI Applications
Install AI-Powered Malware Detection
Conduct Ethical Hacking in AI Systems
Use Proven Ethical Hacking Techniques for AI Security
Ensure Responsible Disclosure of AI Security
Design and Review AI Security Checklist for Enterprises

A detailed Higgins AI Directive White Paper can be downloaded and will address many of these topics in the list.

Artificial Intelligence security is critical for success and must accompany any sized enterprise AI strategy.

Validating AI Controls in Business to Maximize Security

Let’s take a look at how AI can be securely implemented into company operations. Review this slideshow to see real-life examples !

These are only quick snapshots of the main steps to ensure success in any enterprise-wide Artificial Intelligence and Machine Learning initiatives.

Subscribe and get weekly to gain insights and examples of how AI can ‘securely’ change your everyday for the better !

Get Empowered! Take Action!

Just 30 minutes can start you on the path to effectively integrate AI into your business.

We care so much about your time. To that end, this is what you will get from the session:

Personalized free detailed AI integration proposal.
Tools and insights on how you can unlock some of the solutions to the problems that you are facing today at home, work or life.
Introduction to simple systems that have been proven over decades to quickly improve how you tackle your top-of-mind challenges and more importantly, how feel about them.
Free Higgins AI App Standard demo with your data.

All it takes is one step to begin the process of quickly, safely and securely integrate AI into your everyday. Schedule some time with us today.

We are looking forward to hearing from you!

Can AI replace your job ?

There is a growing concern that AI will start taking jobs - in some cases, individuals and businesses are shunning it for the sake of waiting until the benefits can be better established and most risks minimized.

This episode will address some of these concerns and begin unraveling the potentially positive impact of AI on jobs.

What’s the Source of the Fear of AI

AI is slowly taking over many manual tasks like writing summaries, researching topics amongst many other high-energy long winded tasks. Some capabilities are more advanced, yet in the majority of cases, the AI is removing hours and even days of tedious work, making our work more efficient. At least that’s the promise.

Yet even though many can grasp some aspect of what AI can do, it usually evokes a sense of uncertainty and even fear in some. After some discussions with companies, executives and different subject matter experts. there are several reasons for this. The most probable sources for the sometimes tepid response to AI can be segmented into:

Lack of clarity of how AI can be specifically beneficial.

While there are many examples of how AI can help, many don’t know how it can specifically help them at work or at home. Apart from being a glorified search engine, note summarizer, information gatherer, the actual specific use case for how to use AI is not always obvious.

Too many risks for unproven rewards.

Many executives have informed me that the risks of data leaks, erroneous or misleading answers and overall distractions from doing the day to day work required for their teams to meet the deliverables are huge roadblocks for why AI needs to be put on hold until it’s more mature.

Time and cost of implementation.

There is a common perception that these complex AI systems require critical infra-structure rot be built, specific expertise hired and modifications to existing systems required in order for AI to be benefit. This drains resources, time and money that could be used to just get the job done in the traditional manner.

Loss of staff and jobs due to AI implementation.

Observations on the Impact of AI

Many I speak to fear that AI can impact almost any job and so it’s difficult to know whether it’s impact is positive or negative.

While many of the concerns above are evident in professionals, the major, overarching concern is loss of staff and control. Since AI works at such a rapid rate and advances without any seeming limits, letting AI enter the workflow could make the team dependent, lose control of outcomes and expendable at some point.

Some professionals I spoke to stated, and I paraphrase:

“There is way to control the information being inputted and released using the AI.”

“Love the tech. Just can’t see a reasonable use case that makes sense given the early stage of this technology.”

“The technology is too young and wild for enterprise-level regulated operations.”

“I need my team to think for themselves and not be mislead by an AI that doesn’t really think, just regurgitate.”

“We’re just going to wait until the AI fads settle and the technology gets serious.”

Another business owner just used one word to respond to the suggestion that AI could help their business.

The e-mail that was promptly returned just said,” No! ”

There is still so much more that has been communicated, yet these are the most common thoughts collected thus far on why AI is avoided in some organizations.

Leveraging AI in Positive Ways

There are many ways to leverage AI in constructive ways. Chances are, you haven’t heard about most of them. The key distinction between many applications is whether they enhance the way you work or whether they remove a critical aspect of your daily tasks that should be done by you.

How can we leverage AI in a positive way? The answer depends on the job. A breakdown of the major job activities are outlined as follows:

So according to the Harvard Business Review, their 3-year study revealed that knowledge workers (like scientists, engineers etc.) spent “ 41 percent of their workday on <discretionary activities> that require little of their specialized expertise” (HBR Reference).

Imagine if AI could reduce 20% of that work ? Just 20% could give you back almost one day of the week - a full day to innovate further, to apply the true expertise you were hired for, to do the work you are passionate about.

That’s the power of AI. Big picture, that’s what it can do for you - to give you the space and time to do the work you were meant to do.

So can AI take your job ? Not really. Only you can create and innovate in your profession. Yet it can take away the <discretionary activities> we call “Low Value-Added Tasks” that require little or no specialized expertise that the Harvard Business Review was studying for over three years (HBR Reference).

The next section and this weekly Newsletter will provide practical, implementable use case examples of how AI can tackle these more menial tasks to validate it’s use in everyday work.

Validating AI in Business to Minimize “Low Value-Added Tasks”

Let’s take a look at how AI can be implemented into your everyday tasks. Review this slideshow to see real-life examples !

Click The Image To Download the Full Report

These are only quick snapshots of what AI can do. Subscribe and get weekly to gain insights and examples of how AI can change your everyday for the better !

Get Empowered! Take Action!

Just 30 minutes can start you on the path to effectively integrate AI into your business.

This is an opportunity to leave with a confidential personalized plan and your own free Higgins AI install so you can proceed to effectively integrate Higgins AI into your everyday. It's our way of appreciating your valuable 30 minutes.

We care so much about your time. To that end, this is what you will get from the session:

Personalized free detailed proposal.
Tools and insights on how you can unlock some of the solutions to the problems that you are facing today at home, work or life.
Introduction to simple systems that have been proven over decades to quickly improve how you tackle your top-of-mind challenges and more importantly, how feel about them.
Free Higgins AI App Standard demo with your data.

All it takes is one step to begin the process of quickly, safely and securely integrate AI into your everyday. Schedule some time with us today.

We are looking forward to hearing from you!