This assignment focusses on a large logistics organisation that was established 20 years ago and consists of more than 200 staffs. The head office of the organisation is in Sydney yet, the operations are carried out from several states of Australia and other countries of Oceania region. The organisation provides logistics solution to other companies in the fields of warehousing, mining and manufacturing. However, the client companies wants the organisation to provide AI based logistics solution. As a result, the organisation is trying to find options so that it can provide AI based logistics solution to its client companies. The objectives to be achieved in the report are to investigate the new technology and the types of application services that it can provide to its clients in logistics industry.
To investigate on Artificial Intelligence, information from the internet will be used. The following paragraphs will deal with a brief explanation of Artificial Intelligence and the five different types of application that uses Artificial Intelligence. This emerging technology is being used different companies that is replacing human employment with machines. The following paragraphs will discuss the emerging technology in details and investigate five applications that can be offered to clients of the organisation as a solution to the logistics issue. Based on the five applications of AI, three will be proposed that will be helpful for the mentioned organisation to expand its logistics business in the next five years. The report will also consider the advantages and disadvantages of the various applications chosen followed some recommendations for the specific organisation.
Definition of Artificial intelligence (AI):
Artificial Intelligence is defined as the method by which a machine or combination of machines take intelligent decisions just like the humans (Russell & Norvig, 2016). The machines have the ability to learn on their own and based on the datasets take correct decisions. The process by which the machines learn on their own is called machine learning (Michalski, Carbonell & Mitchell, 2013). The technology is growing as time moves ahead and is being discussed about in daily life. The two terms that are commonly used related to AI are machine learning and robotics technology. AI is helping ecommerce to manage its logistics and shipping. The delivery of items are assumed to be made through machines. Amazon is developing a drone-based delivery system known as Amazon Prime Air (Nilsson, 2014). Easy supply chain management will benefit the organisations using AI for logistics management.
Logistics is defined as the steps from producing the products to its delivery. It is the management of product from suppliers to customers (Maleki & Askarzadeh, 2014). All the aspects of the chain of production like financing, distribution, transportation and design are included in logistics management. Previously, logistics was used by military for on-time delivery of weapons to the soldiers. However, it has now become an important way of managing supply chain in most of the organisations. The characteristics of logistics are just in time delivery of inputs along with coordinating flow of information. AI is helping in the easy management of logistics by replacing the humans with machines.
Figure 1: The Logistics Trend Radar
(Source: Staff, 2018)
Five Applications using AI in logistics:
As the head of ICT the following applications of Artificial Intelligence are enlightened that are used to manage logistics. The areas where the new technology finds application are:
- Supply Chain Planning (SCP): Supply Chain Planning is an important part of logistics management. With the help of intelligent work tools, concrete plans can be build that is essential in today’s world. It will also help to forecast within demand, supply and inventory. Optimization and agility in supply chain decision-making can be achieved by correctly using supply chain planning. The SCM professionals will be able to propose best possible scenarios using intelligent algorithms as well as analysis of big data sets. This will facilitate in optimizing product delivery along with balancing between supply and demand. One such company using Supply chain planning is Specialised Logistics Australia.
- Warehouse management: The organisation was facing problem in stocking. Therefore, robots is the solution to this problem. Warehousing is an important part of logistics that influences Supply Chain Planning. SCP is highly dependent on proper inventory and warehouse management. It helps in eliminating the warehouse stocking issues of overstocking and understocking. The self-improving output and the endless loop of forecasting is helping to reshape the warehousing of the organisation. Companies like Toll, Australia post and DHL are using this type of applications.
- AI for developing autonomous vehicles for logistics and shipping: Direct Worldwide Logistics Pty Ltd., is another company using AI for managing logistics. AI will help in reducing the time the company is spending on its delivering and shipping of the products to the destination. Faster and accurate shipping will also help in reducing the lead times and the expenses required in transportation, decreases the labour cost and widens the gap between competitors. Human drivers are restricted to 11 hours driving per day with 8 hours of break a day. However, driverless truck will be able to drive 24 hours a day. This will double the time of delivery of products and services and effectively double the output.
- Robots for Procurement of operations in the organisation: Yusen Global Logistics is using AI based robots. AI will help the organisation speak to suppliers, place purchasing requests, send and set actions with suppliers for the compliance and governance of materials.
- AI and Predictive Analysis for the proper selection of Supplier and Supplier Relationship Management (SRM): AI will aid IFC Global Logistics as it provides the details of each supplier in every supplier organisation interaction. Selection of supplier and sourcing from the right supplier is significantly necessary for the supply chain sustainability and maintaining supply chain ethics. Machine Learning will help in gathering the related information of each suppliers that will help in predictive analytics. The information will be available for human inspection and will be generated by automation of machine-to-machine.
Companies in Australia that are using AI:
Several companies in Australia are using Artificial Intelligence for managing freight logistics and game simulations. For example, Tip Top Bakeries is using Artificial Intelligence software for freight logistics and game simulations is used at the University of Wollongong and Macquarie University. They were among the winners of 2014 iAward held in New South Wales. Tip Top Bakeries required AI to improve its delivery network, increase efficiency of delivery and save logistics cost. It developed a ‘Cost to Serve Solution’ that uses AI software to optimize streamline of its delivery system.
AI in transportation:
It has been assumed that Artificial Intelligence will replace the traditional human drive cars with automated driver-less cars. This will increase the efficiency of driving as it will be driven either by robots or with the help of a software. This will also facilitate just on time delivery of products and services by the organisations. However, experts like Elon Musk and Stephen Hawking feared that unless the potential risks of AI are eliminated it would pose a great threat to civilization. AI has transformed transport industry into a data driven industry.
AI in mining:
Mining industry is described as a heavy industry and therefore, utilizes the AI to develop autonomous vehicles for operating in controlled mining environments (Milne & Witten, 2013). AI is innovating new methods in the process of mineral exploration. Autonomous equipment are well developed in the existing mines that are delivering good benefits (Baker & Inventado, 2014). Smart equipment along with autonomous equipment is changing the industry. New operations in mining are being innovated with the help of AI (Walker, 2018). Mining industry has to invest lot of money for buying a large equipment for mining operations. Shift to the AI technology will help to reduce the expenses in this particular industry.
AI in manufacturing:
Vision of the machines used in manufacturing are being changed by the use of AI. Cameras have been installed in the machines that are more sensitive than human eye. Additionally the camera has the characteristics of sensing the images. Machine vision tools have been developed to find the microscopic defects in the products. One of the major challenges faced by the manufacturing industry while using AI is training the robots and implementing programs in them such that they can sense the happenings around the world. AI helps in developing self-driving forklifts and conveyors that will move materials and finished goods around in the manufacturing factory.
Artificial Intelligence for Warehouse management:
Supply Chain Planning is highly dependent on proper inventory and warehouse management. It helps in eliminating the warehouse stocking issues of overstocking and understocking (Omatu et al., 2014). The self-improving output and the endless loop of forecasting is helping to reshape warehouse management. AI is developing automated vehicles that will sense the availability of spaces in the warehouse and accordingly stock the products in them. This will help them to reduce the stocking issues that warehouse industry face. AI helps making best use of the available spaces in the warehouse.
Three AI based applications that will help the organisation to expand its logistics business in the next five years:
The three applications of AI that will help the organisation to expand its logistics business in the next five years are Driverless truck for delivering product just on time, automated conveyors and using robots for stocking in the warehouse. The following paragraphs will explain the advantages and disadvantages of each application of AI in logistics.
Advantages, disadvantages and risks of using Unmanned trucks for delivery:
The advantages of using AI in transportation are:
- Uber proposed a driverless truck that drove for 120 miles at 55 mph without any issues ("The Future of Artificial Intelligence (AI) in Manufacturing", 2018). The technology was proposed in October 2016. This will decrease the cost of labour and provide higher profits for industry players.
- It is also assumed to reduce the accidents and improve safety of the vehicles (Karaboga et al., 2014). The major issue that human driven cars and trucks face is traffic accidents at night that will be eliminated by the use of smart unmanned vehicles.
- Some smart unmanned vehicles has additional feature of predicting accidents and the health issues of people around them like heart attacks. After detecting, it gives alert to the emergency services along with the location and the details of diagnosis.
The drawbacks of using driverless cars are:
- The replacement of truck drivers, car drivers, taxi drivers and other drivers of the industry with unmanned cars and trucks will lead to severe unemployment of people (Goncharenko, 2017). Job flow will become a major concern among them.
- Third world and underdeveloped countries will be facing severe problems while implementing driverless cars because the infrastructure of roads are not stable in those countries.
- If one company implements AI then to maintain competence in the industry other companies will also have to implement the same (Rossetti et al., 2013). Therefore, the cost incurred on transport will increase than turnover by 3 – 10%.
The risks of unmanned vehicles that are AI based application as assumed by experts like Elon Musk and Stephen Hawking, is the difficulty in maintaining and repairing the faulty trucks and cars. Most of the transportation company will lack the infrastructure to support its maintenance.
Advantages, disadvantages and risks of using automated conveyor belts:
The advantages of using this are:
- The transport of materials within the mines has been made fast by the use of automated machines.
- This would reduce the pressure on labours working in the mines.
- Artificial Intelligence has the capability to sense the availability of materials in the mines and help in fast drilling of coal and other fossil fuels.
- Ensures safety and wellbeing of the workers.
The disadvantages of using AI in mining industry are:
- Unemployment of workers by replacing them with automated machines.
- If the machines become faulty, then workers will not have enough expertise to detect them and therefore, work may be delayed.
The risks involved in this process are delay in production, increase in expenses of maintaining the machines.
Advantages, disadvantages and risks of using robots for stocking in warehouse:
The advantages of using robots for stocking are:
- Eliminates the issues of overstocking and understocking.
- Helps in managing the available spaces in the warehouse properly.
- Eases the process of stocking as the machines aided with AI will sense space and then stocks the materials (Moro, Cortez & Rita, 2015).
The disadvantages are:
- Training the robots to perform the specific actions and implementing programs in them is a tedious job.
- The workers in the warehouse needs to be trained so that they can support the automated machines and repair if any fault occurs.
Artificial Intelligence is after all designed by humans. Therefore, some error might occur in the design of robots, which will make their performance unreliable. Risks will remain in the use of this technology that reduces the quality of performance.
Ethical, social and legal issues related to use of AI in logistics:
The advent and implementation of the new technology will completely transfer the society and will have a major impact on Industrial revolution (Krigsman, 2018). However, it might adversely affect the society by increasing the rate of unemployment among the people. It is also increasing the complexity of life of people. The ethical issues related to the use of Artificial Intelligence in logistics are development of dangerous weapons that will adversely affect the world. Some laws guide the distribution and transportation of materials using AI in logistics however, industries still face frauds with distribution.
From the above discussions, it can be concluded that the purpose of the report is to investigate the applications of AI in expanding the logistics business within five years. According to the investigation, it has been found that AI finds application in mining industries, transportation and warehousing. All the three applications will help in expanding logistics within five years of the particular company. The limitations will be in the implementation of the technology. Experts needs to be hired by the organisation such that AI is implemented properly in the company. AI in transportation will facilitate just on time delivery of products and services by the organisations. They will reduce pressure on the organisation as automated machines perform all operations. Machine vision tools have been developed to find the microscopic defects in the products. One of the major challenges faced by the manufacturing industry while using AI is training the robots and implementing programs in them such that they can sense the happenings around the world. New operations in mining are being innovated with the help of AI. Mining industry has to invest lot of money for buying a large equipment for mining operations. Some smart unmanned vehicles has additional feature of predicting accidents and the health issues of people around them like heart attacks. After detecting, it gives alert to the emergency services along with the location and the details of diagnosis.
The recommendations that the organisation should follow in order to expand its logistics business are:
1. The automated conveyors with daily wear and tear will breakdown, as a result, a monitoring program should be implemented in the industry to supervise the working of the automated conveyors. This will help them to see the conveyor faults before they create a problem in mines.
2. Before implementing the driverless trucks, the company will have to undertake various tests to ensure safety of the vehicle. The tests should ensure vehicle’s perception, response functionality, capabilities of sharing information, privacy of the users and security from hacking.
3. The robots that will be used in warehouse should be programmed properly such that it performs the specific tasks. Interaction between the robots and humans should be harmless.
4. The in-charge of logistic should have enough knowledge of Artificial Intelligence and therefore, the company should hire highly qualified employees.
5. Capital invested for logistics should be such that the organisation can afford the above AI based applications to avoid further ethical dilemmas.
Baker, R. S., & Inventado, P. S. (2014). Educational data mining and learning analytics. In Learning analytics (pp. 61-75). Springer, New York, NY.
Barrat, J. (2013). Our final invention: Artificial intelligence and the end of the human era. Macmillan.
Driankov, D., & Saffiotti, A. (Eds.). (2013). Fuzzy logic techniques for autonomous vehicle navigation (Vol. 61). Physica.
Goncharenko, T. O. (2017). ARTIFICIAL INTELLIGENCE: PROS AND CONS (Doctoral dissertation, ???????????? ?????????? ???????????).
Karaboga, D., Gorkemli, B., Ozturk, C., & Karaboga, N. (2014). A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artificial Intelligence Review, 42(1), 21-57.
Krigsman, M. (2018). Artificial Intelligence: Legal, ethical, and policy issues | ZDNet. Retrieved from https://www.zdnet.com/article/artificial-intelligence-legal-ethical-and-policy-issues/
Liao, H. J., Lin, C. H. R., Lin, Y. C., & Tung, K. Y. (2013). Intrusion detection system: A comprehensive review. Journal of Network and Computer Applications, 36(1), 16-24.
Maleki, A., & Askarzadeh, A. (2014). Comparative study of artificial intelligence techniques for sizing of a hydrogen-based stand-alone photovoltaic/wind hybrid system. international journal of hydrogen energy, 39(19), 9973-9984.
Michalski, R. S., Carbonell, J. G., & Mitchell, T. M. (Eds.). (2013). Machine learning: An artificial intelligence approach. Springer Science & Business Media.
Milne, D., & Witten, I. H. (2013). An open-source toolkit for mining Wikipedia. Artificial Intelligence, 194, 222-239.
Moro, S., Cortez, P., & Rita, P. (2015). Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with Applications, 42(3), 1314-1324.
Nilsson, N. J. (2014). Principles of artificial intelligence. Morgan Kaufmann.
Omatu, S., Bersini, H., Corchado, J. M., Rodr?guez, S., Pawlewski, P., & Bucciarelli, E. (2014). Distributed computing and artificial intelligence. Springer International Publishing.
Rossetti, R. J., Almeida, J. E., Kokkinogenis, Z., & Gonçalves, J. (2013). Playing transportation seriously: Applications of serious games to artificial transportation systems. IEEE Intelligent Systems, (4), 107-112.
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,.
Staff, 2. (2018). Transforming Logistics with Artificial Intelligence - Supply Chain 24/7. Retrieved from https://www.supplychain247.com/article/transforming_logistics_with_artificial_intelligence
The Future of Artificial Intelligence (AI) in Manufacturing. (2018). Retrieved from https://www.autodesk.com/redshift/future-of-artificial-intelligence/
Walker, J. (2018). AI in Mining - Mineral Exploration, Autonomous Drills, and More. Retrieved from https://www.techemergence.com/ai-in-mining-mineral-exploration-autonomous-drills/