May 16, 2020

Honda invests $1m is young manufacturers and engineers

Honda
People and Skills
Manufacturing Employees
Young Man
Glen White
4 min
Honda: The Power of Dreams
Honda has announced plans to roll out an innovative $1 million workforce development initiative to create interest in manufacturing careers and provide...

Honda has announced plans to roll out an innovative $1 million workforce development initiative to create interest in manufacturing careers and provide educational and training opportunities to prepare the next generation workforce for high-tech positions in the manufacturing industry. The initiative will be based in Ohio, US.

The new program, called EPIC, is designed to proactively address the skills gap in US manufacturing and includes programs for middle school to community college students as well as initiatives for current manufacturing associates at Honda.

This EPIC program draws its name from the four key areas of the initiative:

  • Creating Enthusiasm about manufacturing among middle school students;
  • Encouraging Passion among high school students to harness the power of technology;
  • Promoting Innovative instruction at two-year colleges; and
  • Continuing Commitment to further educational opportunities for Honda associates.

According to a study by Deloitte and the Manufacturing Institute, over the next decade, there will be a need for more than 3.4 million manufacturing jobs. And based on continued job creation and an aging workforce, two million of those jobs – nearly 60 percent – will go unfilled because prospective employees lack interest or essential skills.

“This initiative is geared toward creating interest in manufacturing as a career at the middle school, high school and college levels and then providing continued opportunities in the workplace,” said Rick Schostek, executive vice president of Honda North America. “We realize manufacturing has always been key to America's economic strength and we want to implement programs that create opportunities not only for ourselves, but for every company with an interest in U.S. manufacturing.”

As one effort to create enthusiasm among younger students, Honda worked with Edheads, a Hilliard, Ohio educational game developer, to create a first-of-its kind manufacturing video game designed for classroom use. The game teaches logic, critical thinking and takes the user right to the engine manufacturing line where they apply math and problem solving skills to find answers to real world problems.

Other program elements aimed at creating Enthusiasm for manufacturing include:

  • Engineering on wheels – Honda is partnering with businesses and schools to facilitate "hands-on" manufacturing activities in six mobile labs.  These labs feature production robotics and provide students with an opportunity to experience real-world manufacturing technology.
  • Summer STEM "Techie" camps – Honda will work with TechCorps to sponsor full-day, week-long summer camps that will allow students to immerse themselves in STEM-related activities, computer programming, and web and app development, all in a fun-filled environment.

To encourage Passion for manufacturing among high school students, Honda has partnered with two entities to create opportunities including new curriculum, equipment and opportunities to visit Honda facilities.

  • Honda will nominate and help fund up to five schools in Union, Logan and Shelby counties to become part of the SME (Society of Manufacturing Engineers) Education Foundation PRIME initiative.  The participating schools will receive funding from Honda for advanced curriculum and support of STEM activities.
  • Honda is supporting the Marysville Early College STEM High School, which was developed through a collaborative partnership with Marysville schools, Columbus State Community College, Ohio Hi Point Career Center, Honda and the Union County Chamber of Commerce.  The project was funded with a State of Ohio "Straight A Fund" grant. Honda has worked with the school to select lab equipment, lay out the space, select an instructor and develop the curriculum for the manufacturing pathway.  Honda technicians and engineers are also creating opportunities for the students to learn about these exciting manufacturing careers through tours and know-how sharing.

Honda is also partnering with area two-year colleges to provide incoming high school students with opportunities and Innovative programs.

  • Honda is announcing twelve, $2,500 scholarships for students pursuing an associate degree in Manufacturing or Mechanical Engineering Technology from local college institutions (Rhodes State, Columbus State, Marion Technical, Edison Community, Sinclair Community and Clark State).
  • Honda will expand the work-study pilot program that it developed with Columbus State Community College.  This program allows students the opportunity to work at Honda three days a week, while taking classes two days.  This provides students with an opportunity to build technical skills while earning their degrees. Honda will expand the pilot from three students to 18 and work with the Ohio Board of Regents to expand the program to other college partners.

Additionally, Honda's Commitment to providing on-going technical training for its associates is on display with two new technical development centers.  These centers provide the opportunity for associates to train on the latest manufacturing technologies and build on the skills and knowledge they have gained throughout their careers.  These centers, one for powertrain at the Anna Engine Plant and another for vehicle production near the Marysville Auto Plant, are designed to help operational and equipment maintenance associates gain the expertise necessary for the high-tech machinery utilized in manufacturing settings.  Further, a training curriculum includes basic fundamentals as well as advanced training for specialized areas. These training initiatives are part of Honda's commitment to its associates to keep them up-to-date on the latest production technology in the industry.

"The investment we are making in this EPIC initiative is the culmination of many creative partnerships we have forged with educators, businesses and Honda associates to help design this program," said Schostek.  "This robust and innovative initiative is designed to be used by Honda and supplier operations in other regions of the country."

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May 11, 2021

5 Minutes With PwC on AI and Big Data in Manufacturing

SmartManufacturing
ArtificialIntelligence
bigdata
Technology
Georgia Wilson
6 min
PwC | Smart Manufacturing | Artificial Intelligence (AI) | Big Data | Analytics | Technology | Digital Factory | Connected Factory | Digital Transfromation
Manufacturing Global speaks to PwC on the application of artificial intelligence (AI) and Big Data in Manufacturing...

Please could you define what artificial intelligence is, and what Big Data is?

AI is the ability of a machine to perceive its environment and perform tasks that normally require human intelligence, and it’s a whole field of different technologies, techniques and applications. 

Big data is a set of tools and capabilities for working with, for processing, extremely large sets of data. 

How does AI and Big Data work together?

Big data is just one of the enablers of AI, though as we see increasing volumes of data, it’s one of the most important 

 How can this be applied to a manufacturing setting?

Broadly speaking, there are many benefits of AI, and the use of data, which include reducing costs, minimising human error, and increasing productivity and efficiency. The important thing to consider is any setting - for the use of any technology - is what is the problem you are trying to solve? Be it merely automating repetitive tasks or to reinventing the nature of work in factories by having humans and machines collaborate in order to make better and faster decisions.  

Why should manufacturers use AI and Big Data when adopting smart manufacturing capabilities, what is the value for manufacturers?

One view is, again, the economic benefits of AI, which come in manufacturing as a result of: 

1. Productivity gains from automating processes and augmenting the work of existing labour forces with various applications of AI technologies. 

2. Increased consumer demand due to the increased ability to personalise and tailor manufactured products, along with higher-quality digital and AI-enhanced products and services. 

Manufacturing (and construction industries) are by nature capital intensive, and in our 2018 report, “The potential impact of AI in the Middle East,” we estimated that the adoption of AI applications could increase the sectors’ contribution to GDP gains by more than 12.4% by 2030. 

How can AI and Big Data help manufacturers to evolve in the Industry 4.0 revolution? What about those already looking at Industry 5.0?

It’s really about the investment you make now, in order to futureproof your business. 

We typically see two broad strategies or approaches to the adoption of AI. There are things that we can do immediately, without any recourse to Big Data - which is to adopt technologies we describe as Sensing, those involving computer vision, for example. There are plenty of use cases where these can be used immediately in manufacturing, such as for automatic fault detection. However, there is a longer term play which requires investing in data - getting the right collection mechanisms in place, storage, data governance, Big Data capabilities etc - in order to develop increasingly valuable machine learning driven AI use cases. This is absolutely necessary for long term adoption success. 

What is the best strategy for organisations looking to realise the value of AI and Big Data in manufacturing?  

AI and Big Data are only one part of a successful smart factory. The organisations that lead on AI adoption are those who have already made the most progress in digitising core business processes. In order get ahead in using AI solutions at scale, there are a number of technology investments and organisational decisions to be made, including: 

1. Digitising processes ultimately leads to improved ability to generate data, and in the manufacturing setting - with many 100s of sensors generating 1000s of measurements in real time, the result is Big Data. Data is key to building AI so reliable and accurate data acquisition, management and governance are key. The production line and factories play a critical and direct role in the data-acquisition process. 

2. AI strategy, both long and short term, begins with the use cases, the business applications. Manufacturers need to ask where they want to use AI and gather these use cases together and prioritising projects based on a balance of expected impact and complexity of implementation. 

Of course, in addition to technology and business processes, people are at the heart of any successful technology adoption. AI teams need to be composed not only of data scientists, also data engineers and solution architects to enable their work, data stewards to ensure accuracy, and increasingly so call “Analytics/AI translators” who are able to communicate with business leaders and technology experts. Culture is also key, and manufacturers need to enable a data and AI-driven culture, building trust in data and algorithms by educating their workforce about AI and its capabilities, how best to extract value. It’s not just the positive of course, but also the risks and limitations, as these when encountered without expectations having been set, can significantly impact willingness to invest. 

What are the challenges when it comes to adopting AI and Big Data in manufacturing?

PwC research has shown that one of the major challenges to implementing AI is uncertainty around return on investment (ROI). As I said, there is significant investment required for a long term data and AI strategy to be successful, and expectations around the time to see tangible returns must be set realistically. 

Many companies also struggle with the data side: collecting and supplying the data that an AI system needs to operate, and ensuring that it is accurate. Again, this speaks to the bigger investments required in digitisation. 

Some of the main challenges for manufacturing companies with implementing AI at a scale from our research include:  

  • 40% → Technologies not mature  
  • 40% → Workforce lacks skills to implement and manage AI  
  • 36% → Uncertain of return on investment  
  • 33% → Data is not mature yet 
  • 32% → lack of transparency and trust  
  • 24% → Work councils and labour unions  
  • 22% → Regulatory hurdles in home & important markets  

One element highlighted here, particularly around lack of trust, and labour unions, is that AI is typically misrepresented in the media as “replacing” workers, and taking jobs. Yes, there are efficiency gains to be made from automation, as there have been since the first industrial revolution. But we believe that Data and AI are at their most valuable when they are used to augment workers, enhancing their abilities and the products being manufactured. 

Another challenge we’re starting to see emerge is cyberattacks increasingly targeting interconnected equipment and machinery in smart factories. PwC recently hosted a webcast, in cooperation with the National Association of Manufacturers in the US and Microsoft to discuss this. 

What are the current trends in AI and Big Data in manufacturing?  

  • We see companies putting slightly more focus on adding AI solutions to core production processes such as the engineering, and assembly and quality testing 
  • Safety is of significant importance, with techniques adopted in protocol adherence capabilities (for example maintaining safe distance from specific machinery) being adopted in more every day scenarios for COVID-19 protocol adherence 
  • There is considerable interest in predictive maintenance for large machinery involved in manufacturing processes, and also supply-chain optimisation

What do you see happening in the AI and Big Data industry in manufacturing in the next 12-18 months? 

Honestly, I think we’ll see a continuance of where we’ve already been going for the last 12- 18 months. AI and data are already being used in manufacturing but this use doesn’t get as much attention in the media as, say, healthcare, but the success stories are there, and they will continue as operations continue their digital journeys. 

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