AI | Delta Bravo AI

Knudt Flor, former CEO of BMW Manufacturing, Joins Advisory Board of Delta Bravo Artificial Intelligence

ROCK HILL, SC, January 5, 2023 – Knudt Flor, former CEO of BMW Manufacturing, Joins Delta Bravo Artificial Intelligence to Drive Smart Factory Adoption

Retired BMW Manufacturing CEO Knudt Flor has been appointed to the newly created advisory board at predictive analytics company Delta Bravo.

Prior to retiring in September 2021, Flor oversaw BMW Plant Spartanburg, the largest BMW Group plant in the world. The South Carolina factory exports more than two-thirds of its models to 125 global markets. For seven consecutive years, it has been the largest exporter by value in the United States. The model portfolio includes five top-selling BMW X models, four Motorsport X models, and two plug-in hybrid electric X models. During Flor’s tenure, BMW released four new vehicles, the BMW X7, X3 M and X4 M, and the BMW X3 xDrive30e, as well as next-generation models for the BMW X3, X4, X5, X5 M, X6, and X6 M. Flor is the second-longest serving president of BMW Manufacturing.

Flor was introduced to the Delta Bravo team through the South Carolina Council on Competitiveness. “When I met the Delta Bravo team, I was immediately impressed by what they were doing,” said Flor. “The next wave of successful manufacturers will leverage data to improve operations and workforce readiness. Delta Bravo accelerates this process in a way that enhances the operation instead of disrupting it. I’m fascinated by the innovative work they’re doing, and excited to work alongside Rick and team.”

“We are very fortunate to have someone of Knudt’s caliber on our Advisory Board,” said Rick Oppedisano, founder and CEO of Delta Bravo. “He’s had a front-row seat for the evolution of manufacturing technology and brings decades of experience and perspective on the current challenges facing OEMs and suppliers. From the very start when we were introduced, it was clear he had ideas that would add value to our current and future customers. We’re thrilled to have him.”

Flor has also been vice president of production at BMW Plant Munich, director of BMW Plant Rosslyn in South Africa, senior vice president of corporate quality for the BMW Group, and senior vice president of Manufacturing at BMW Brilliance Automotive Joint Venture in Shenyang, China. In January 2022, Flor joined the College of Charleston as senior vice president of innovation and industry engagement.

“I have been in industry for more than 30 years, and I’ve seen and lived through the big transformation on the shop floor,” Flor said. “In the 1990s and early 2000s, automation and lean production gave us a big jump in productivity, quality and competitiveness. Machine learning and AI will have the same big impact — and it will be a radical change again.”

Manufacturing CEOs across the world are embracing Machine Learning and AI to drive the transformation, but research firm Gartner estimates an 80% failure rate for first-time AI projects.

“I’ve chosen to partner with Delta Bravo after seeing the impact of their solution firsthand,” said Flor. “They’ve spent five years building their product and practice around the needs of the manufacturer. They are an ideal solution for midsize manufacturers in the supply chain as well as larger OEMs.”

ABOUT DELTA BRAVO ARTIFICIAL INTELLIGENCE

Headquartered in Rock Hill, South Carolina, Delta Bravo helps manufacturers turn data into Predictive Models that reduce downtime and waste while increasing quality and throughput. The company’s flagship product, the Delta Bravo platform, empowers rapid data transformation and offers several options for integrating machine learning and AI solutions into existing manufacturing processes and systems. Delta Bravo has empowered greater operating margin and workforce readiness for customers like Rolls-Royce, AccuWeather, Nucor Steel, Toyota, Continental, Gulfstream and more since 2017. For more information, please visit Delta Bravo’s website at https://deltabravo.ai.

FOR MORE INFORMATION:
Ashley West, Delta Bravo
Ashley@deltabravo.ai

Partnership Announced Between Cisco Systems (CSCO) and Delta Bravo Artificial Intelligence

ROCK HILL, SC, October 25, 2022 – From over 50,000 worldwide Cisco partners, Delta Bravo Artificial Intelligence among 13 selected for Digital Solutions Integrator Program

Improving production throughput and workforce readiness for manufacturers while reducing waste is the focus of a new partnership between Delta Bravo Artificial Intelligence and Cisco Systems (CSCO).

Delta Bravo Artificial Intelligence, Inc. today announced it has joined the Cisco® Digital Solutions Integrator (DSI) Program. The DSI Program selects strategic partners from Cisco’s worldwide partner network to provide unique value and perspective to Cisco’s most important customers. Out of over 50,000 Cisco partner companies worldwide, less than 20 are selected for the DSI Program.

“Cisco DSI Partners are at the forefront of digital transformation. It’s all about driving new digital conversations, and DSIs help partners quickly steer those discussions to the ‘why’. They help the customer define the digital journey in terms of investments and business outcomes,” says Nick Larison, DSI Business Development Manager. “Delta Bravo plays that role for manufacturers moving towards the smart factory. Our partnership provides an opportunity for Cisco customers to work with an industry leader, and truly benefit from integrating data across the plant floor.”

Delta Bravo works with manufacturers like Rolls-Royce, Continental, Nucor Steel and more to improve throughput and quality while reducing waste and unplanned downtime. “Delta Bravo empowers smart manufacturing by bringing data together across operations, using machine learning and AI to spot improvement opportunities,” says Rick Oppedisano, CEO of Delta Bravo. “We improve workforce readiness with tools that help operators make better decisions faster.”

Cisco will work with Delta Bravo to provide manufacturing customers a Best Practice network and security architecture to support IoT, predictive analytics and artificial intelligence efforts across multiple plants and facilities.

A Fortune Business Insights™ report titled, “Smart Manufacturing Market Share, 2022-2029,” expects the global smart manufacturing market size to grow from USD 277.81 billion in 2022 to USD 658.41 billion in 2029 at a CAGR of 13.1% during the 2022-2029 period. Developing technologies such as Artificial Intelligence (AI), cloud, big data, and Machine Learning (ML) are predicted to drive customer benefit and market growth.

“Manufacturers leveraging machine learning and AI are learning new lessons about the network,” says Oppedisano. “Machine learning models often require more data to be collected more often. Robust network performance is critical. When those models go into production and the business depends on them for daily operations, data sources need to be secured to maintain accuracy and reliability. Cisco’s Best Practice network and security architecture protects the credibility and value of our customers’ smart factory investment.”

ABOUT DELTA BRAVO ARTIFICIAL INTELLIGENCE
Headquartered in Rock Hill, South Carolina, Delta Bravo helps manufacturers turn data into Predictive Models that reduce downtime and waste while increasing quality and throughput. The company’s flagship product, the Delta Bravo platform, empowers rapid data transformation and offers several options for integrating machine learning and AI solutions into existing manufacturing processes and systems. Delta Bravo has empowered greater operating margin and workforce readiness for customers like Rolls-Royce, AccuWeather, Nucor Steel, Toyota, Continental, Gulfstream and more since 2017. For more information, please visit Delta Bravo’s website at https://deltabravo.ai.

FOR MORE INFORMATION:
Ashley West, Delta Bravo
Ashley@deltabravo.ai

3 Lessons Learned in Building a Production AI Platform from Delta Bravo

Modern Devs Charlotte hosts Delta Bravo team for presentation, live ML coding exercise

Delta Bravo‘s John McAliley and Rick Oppedisano presented to a packed house this week for Modern Devs Charlotte‘s monthly meetup at Wray Ward in uptown Charlotte.

“There’s a ton of interest in AI and Machine Learning,” says Oppedisano, “we want to help people understand where they can start and also learn from our journey. The lessons we’ve learned along the way could save them months of technology evaluation and development time and in some cases, thousands of dollars in system costs.”

Start Small with Familiar Tech

The presentation started with some context of how and why the Delta Bravo AI platform was built. This helped articulate a clear AI use case and also defined the differences between data science, machine learning and artificial intelligence. “Determining if you have an AI use case at all is important,” says Oppedisano. “The ability to clarify that use case and establish the measurables behind it is the first step in the process.”

Once the use case is established, the next step is prototyping. The Delta Bravo team recommends to start small and with a technology you’re already comfortable with. “There are a ton of choices out there and it can be a bit overwhelming,” says McAliley. “There’s likely an option in a tech stack that you’re already working with. Start there to save time and focus on a small, controllable and quickly proven use case.”

Sample Use Case, Live Machine Learning Code Exercise

McAliley followed up with a sample AI use case based on Image Recognition and a live Machine Learning code demo designed to show the differences in accuracy based on data quality and model construction.

A model was established based on metrics that were clearly and visibly defined. “Accuracy is synonymous with credibility,” explained McAliley. “This exercise shows how to get the highest degrees of accuracy, as well as where certain compromises exist and where you begin to get diminishing returns on your model.”

The team also shared Delta Bravo’s functional architecture and provide an example of how AI is used within the platform to recognize, quantify and predict an oncoming database performance problem. This helped the audience visualize the differences in and applications of data science (insight), machine learning (prediction) and artificial intelligence (recommended action).

Lessons Learned

Oppedisano and McAliley shared 3 Lessons Learned from their experience, ranging from technical choices to the importance of data. “The quality of the data you are putting into the model is at the heart of everything,” says Oppedisano. “It’s a classic garbage in, garbage out scenario.” The presentation covered some of the more efficient options available for data cleansing and grouping, as well as the importance of representing the data in a clear, visible manner. “In certain scenarios, the AI process presents the data more efficiently than a human,” says McAliley. “Being able to visualize the data itself, then drill down into insight, correlation and action is important.”

Oppedisano and McAliley shared a fourth “Bonus Lesson” about understanding and managing cost projection. “Machine learning requires a lot of processing,” says Oppedisano. “Its easy for cost to start becoming a factor.”

Feedback and Discussion

“Attendee feedback was very positive,” says Oppedisano, “but the real impression we got was how much opportunity there is in this space.” Several potential use cases and solutions were discussed during and after the presentation, with a lively discussion between the attendees and presenters.

“There’s a lot of passion in the AI community at large,” says Oppedisano. “We want to be a part of bringing that passion and knowledge to the local technology community.”

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