Week 5 Case Study 11.1 – John Deere

Read “Case 11.1: John Deere” and write an essay that answers the following questions:

1. What are some of the benefits that John Deere has gained by implementing AI and machine learning in its products and operations?

2. What is the “Farm Forward” campaign, and how does it incorporate AI into John Deere’s machinery?

3. How has John Deere used AI technology to improve the accuracy and effectiveness of its spraying processes, and what are the benefits of this approach?

4. What was the purpose of John Deere’s acquisition of Blue River, and how has it helped to advance the company’s use of AI and machine learning?

5. How has John Deere used AI technology to address welding defects and improve the quality of its products, and what are some of the benefits of this approach?

6. What are some of the competitive advantages that John Deere has gained by adopting AI technology in its business, and how might this impact its future success in the agricultural industry? 

Requirements:

· There is no specific page requirement for your analysis. Instead, your work will be evaluated based on how thoroughly it addresses each of the questions that have been outlined for you.

· You must utilize proper APA formatting and citations throughout your paper. If you use any supporting evidence from external sources, it is imperative that you provide accurate citations for each reference.

· You must include a minimum of two sources from scholarly articles or business periodicals, aside from the course textbook. 

· Include your best critical thinking and analysis to arrive at your justification.    

 

 

Case 11.1: John Deere

John Deere, a company that is almost 200 years old, is applying AI and machine learning in all aspects of its business. Deere is the first mover in the agricultural industry in implementing AI into its products and operations. As a pioneer in adopt- ing AI, John Deere has gained a large competitive advantage over its traditional competitors.

In 2013, Deere revealed its “Farm Forward” campaign, a program focused pri- marily on implementing AI into its machines to create an array of enhanced technology- driven machinery. One example of this advancement is the development of the solely automated self-driving tractor, which is capable of not only driving itself around, courtesy of AI, but is also capable of identifying how much herbicide to spray. John Deere also developed the Autonomous Drone Sprayers. The drone sprayer flies over the fields using a weed scanner and a sprayer to precisely apply pesticides to the crops where it needs to go. Having the weed scanner be able to read and analyze how much pesticide to use on certain parts of the field is a great idea. This is a new way to cut down on the amount of chemicals used on growing crops and, at the same time, decrease cost. Furthermore, Deere is using AI to gather first- hand data to enhance their ability to accurately optimize the advice it gives to farm- ers. Over time, this will increase the farm’s general efficiency, likely increase their revenues, and increase Deere’s competitive advantage (Sarnecka, 2019).

In 2017, Deere acquired a Silicon Valley company Blue River which specializes in computer vision and image recognition. This move has allowed Deere’s machin- ery to interpret images captured by cameras installed in machinery and enable autonomous decision-making using AI technology. This increases the rate at which the plants survive, as the machinery has become more accurate and effective at aid- ing the plant in surviving than the farmer.

Welding is a high-demand industry that suffers from many challenges. AI and machine learning can benefit the agriculture industry and companies like John Deere. Think about the sizes of the agricultural machinery, and even bigger com- bines and balers that farms use, one could imagine that fixing these large machines may take extreme welding. The pieces of iron could be thousands of pounds to lift and hold in the right spot while a high-strength weld is completed. The engineers came up with a new idea to use Intel’s artificial intelligence technology to solve a costly problem in the process. The solution also uses computer vision to automati- cally spot common defects in the automated welding process in its manufacturing facilities. Considering the volume of welds that Deere must produce every day the facility is running, there are bound to be some mistakes. One of the most common problems is when cavities in the weld medal form caused by trapped gas bubbles as the weld is cooling down. These cavities weaken the strength of the weld. With AI technology, Deere and Intel developed an integrated end-to-end system of hardware and software that can generate insights in real time, at levels beyond the human sense’s capability (Sarnecka, 2019). When using a neural network-based inference engine, the solution logs defects in real time and automatically stops the welding process. The automated system allows Deere to correct the issue in real time and produce the quality products that Deere is known for. To put into other words, this technology allows the AI welding machine to sense and stop whenever there has been a mistake in the recently finished welds that are cooling, allowing Deere to fix the problem before it has even been put out into the field and malfunctions.

John Deere is a machinery-based company, and implementing AI into their busi- ness is something most people would not think of connecting. The technology they produce becomes patented and is often improved upon. The technology itself will give Deere a competitive advantage over those who resort to traditional, human- based methods.

 

11 Artificial Intelligence in Manufacturing

http://www.localmotors.com

http://www.localmotors.com

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