Strategy Short Term Strategy
Virtual reality and augmented reality are two latest technologies that are currently being used by different sectors for commercialization and benefitting the existing business system. However, these technologies have only been partially adopted as they are of extremely high costs and very difficult to implement owing to the lack of sufficient knowledge regarding these technologies among the employees. Researchers are finding new ways to reduce implementation cost of the technologies so that they can be applied by different industries.
In this report, the two technologies have been discussed and a product roadmap have been created for a particular manufacturing company.
The short term strategy is to introduce the two technologies virtual reality and augmented reality and limited implementation in the existing operations set up. This will enable the employees to learn more about the working of the two technologies. Moreover, futher later implementation will also be possible after the initial implementation.
The main mission of the organization is to implement virtual and augmented reality in the business operations and also integrate both into one common system that will aid the manufacturing operations.
The use case for the short term plan of the company is shown in the following diagram.
Figure 1: Use Case for Initial Short Term Plan
(Source: Created by Author)
The costs for the short term plan and proposed budget details are shown in the following table.
Program Element |
Element Manager |
2017 |
2018 |
2019 |
2020 |
2021 |
2022 |
2023 |
2024 |
2025 |
2026 |
Technical Upgrades |
Mr. A |
$300,000 |
$250,000 |
$250,000 |
|||||||
Implementation of Virtual Reality |
Mr. B |
$200,000 |
$150,000 |
$150,000 |
|||||||
Implementation of Augmented Reality |
Mr. C |
$300,000 |
$250,000 |
$250,000 |
|||||||
Initial Testing in Operations |
Mr. D |
$400,000 |
$450,000 |
$500,000 |
|||||||
Additional Investments |
Mr. E |
$150,000 |
$150,000 |
$150,000 |
|||||||
Integration of Both Systems |
Mr. F |
$400,000 |
$400,000 |
$400,000 |
|||||||
Program Total Costs By Year |
$700,000 |
$650,000 |
$1,700,000 |
$1,000,000 |
$1,050,000 |
$0 |
$0 |
$0 |
$0 |
$0 |
|
Program Grand Total Cost |
$5,100,000 |
The long term strategy includes complete integration of the two technologies in the system. However, this is not currently possible as these are extremely expensive. Hence, with growing revenues, sufficient funds should be prepared in order to finally approve the implementation plan.
The mission for the long term strategy plan is to complete the implementation of virtual and augmented reality into the entire operations system. The main goal is to integrate both the systems into one common system.
The use case for the long term plan is shown in the following diagram.
Figure 2: Use Case Diagram for Long Term Plan
(Source: Created by Author)
The cost benefit analysis for the long term plan is shown in the following table.
Benefit Sources |
2017 |
2018 |
2019 |
2020 |
2021 |
2022 |
2023 |
2024 |
2025 |
2026 |
Cost Reduction |
$500,000 |
$525,000 |
$550,000 |
$600,000 |
$650,000 |
$700,000 |
$800,000 |
$1,000,000 |
||
Enhanced Revenues |
$250,000 |
$350,000 |
$500,000 |
$600,000 |
$750,000 |
$800,000 |
$900,000 |
|||
Labor Reduction |
$100,000 |
$100,000 |
$100,000 |
$100,000 |
$100,000 |
$100,000 |
$100,000 |
|||
Decreased Overhead |
$50,000 |
$50,000 |
$50,000 |
$50,000 |
$50,000 |
$50,000 |
$50,000 |
$50,000 |
||
Total Benefits Per Year |
$0 |
$0 |
$550,000 |
$925,000 |
$1,050,000 |
$1,250,000 |
$1,400,000 |
$1,600,000 |
$1,750,000 |
$2,050,000 |
Confidence Factor |
100% |
100% |
100% |
100% |
100% |
100% |
100% |
100% |
100% |
100% |
Benefits Claimed for Analysis |
$0 |
$0 |
$550,000 |
$925,000 |
$1,050,000 |
$1,250,000 |
$1,400,000 |
$1,600,000 |
$1,750,000 |
$2,050,000 |
Program Grand Total Benefit |
$10,575,000 |
The product roadmap is shown in the following diagram.
Before developing an integration plan for virtual reality and augmented reality for the manufacturing industry, in-depth analysis of both of these factors and their effects on the manufacturing industry need to be conducted. These are discussed as follows.
Mission and Goals
Virtual reality is an innovation that includes a wide range of thoughts. It characterizes an umbrella under which numerous scientists and organizations express their work. The expression was begun by Jaron Lanier the organizer of VPL Research one of the first organizations offering virtual reality systems. The term was characterized as “a computer created, intuitive, three-dimensional condition in which a man is inundated”. There are three key focuses in this definition (Barfield 2015). To start with, this virtual condition is a computer produced three-dimensional scene which requires superior computer designs to give a satisfactory level of authenticity. One of the recognizing signs of a virtual reality framework is the head mounted show worn by clients. These showcases shut out the whole outside world and present to the wearer a view that is under the entire control of the computer. The client is totally drenched in a simulated world and ends up plainly separated from the genuine condition. For this drenching to seem reasonable the virtual reality framework should precisely detect how the client is moving and figure out what impact that will have on the scene being rendered in the head mounted show (Billinghurst, Clark and Lee 2015). The second point is that the virtual world is intuitive. A client requires ongoing reaction from the framework to have the capacity to cooperate with it in a successful way. The last point is that the client is submerged in this virtual condition.
Researchers created the idea of a VM framework and portrayed the item and process model of a VM framework. In view of the idea and the model, a general modeling and reproduction design for a VM framework was created. Researchers also built up a cutting power expectation model for reproducing machining conditions in VM. VM systems are coordinated computer-based models that speak to the exact structures of manufacturing systems and recreate their physical and educational conduct in operation (Ong and Nee 2013). VM innovation has accomplished much in diminishing manufacturing expense and time-to-advertise, prompting a change in profitability. Much research push to conceptualize and develop a VM framework has been accounted for. A virtual machining research facility for information learning and aptitudes preparing was actualized by Fang et al. (1998). In the virtual machining research facility, both extensive information learning and physical aptitudes preparing can be accomplished in an intuitive engineered condition. By utilizing a VM framework, clients can choose and test distinctive machining parameters to assess and enhance machining forms, and the manufacturing expense and time-to-market can be decreased, prompting a change in profitability. Be that as it may, a useful VM framework is profoundly multi-disciplinary in nature (Wang et al. 2014). Utilizing head-mounted stereo glasses and intuitive gloves, understudies can virtually work a machine or set machining parameters and information CNC G-code program to cut the work-piece consequently, Machining process execution, for example, machining conditions, cutting powers, cutting force, surface unpleasantness and apparatus life, can likewise be recreated with the machining procedure assessment models. Furthermore, some business software for VM, for example, Delmia’s VNC, can reproduce machining forms in a 3D domain and recognize impact. A large number of these examination tasks and business software for VM systems have confinements in their execution. Right off the bat, many machining hypotheses and heuristics should be modeled in a VM framework (Wei et al. 2015). In any case, most VM applications are designed just for particular issues in pre-characterized conditions. Other than geometrical modeling of machines, investigative modeling of machining parameters, for example, the cutting power, additionally must be created for each particular errand. Besides, each developing procedure of another VM framework is similar to the reevaluation of “wheels”. Finally, different VM systems are created with various programming and modeling dialects, making them less adaptable and versatile because of contrariness issues. Any change m one section would require the entire framework to be adjusted.
Use Case
There are a considerable measure of issues that should be comprehended amid the computer helped design (CAD) of items in characterized time. Initially the single 3D sections (singular passages of get together rundown) should be made and depicted in all points of interest. Augmented reality framework gives an intricate view on dealt with territory and applicable procedures. Virtual parts are joined with genuine components (Westerfield, Mitrovic and Billinghurst 2015). It is a common existing of client’s genuine scene together with computer’s virtual scene what is considered as a growth. These strategies for improved client condition discover its usage in numerous modern circles, for instance in range creation of parts from composite materials. 3D CAD model loaded with fundamental data is then prepared to be sent out to arrangement of augmented reality. In next stage the dissected parts should be dealt with and furnished with data about introduction and position, since it should be settled specifically place of the fundamental creation model in the genuine condition. The 3D model involves a pack of data about its properties (geometrical shape, introduction and position esteem, mass properties, material and auxiliary attributes) (Büttner et al. 2017). This information is typically sent to the extraordinary segment of the computation zone of the computer helped designing (CAE) systems. With utilization of these instruments the models can be investigated from various perspectives and proposals can be made concerning appropriateness of geometrical state of the individual parts that are will be incorporated into conclusive get together of the made item. Augmented reality application gives the designer probability to utilize diverse techniques, while the trademark highlight implies the innovation of showing and helping of manufacturing situating.
Programming tools called Virtools depends on standards of question programming, where diverse conditions, activities and relations are recommended for specific protests that as indicated by their capacity change to the alleged building blocks of the application (BBs). Markers are graphical images arranged in following space (working territory). Their area and introduction is gotten utilizing the extraordinary BBs called ART catch. Information is caught on the info pins of BBs and after that the correct data about their positions get to the yield region (Posada et al. 2015). Principles and activities running between singular squares or their areas can be graphically communicated in type of conduct diagram which in the meantime fills in as programming device itself. Usefulness of whole application can be then portrayed through the errands that are acknowledged because of various conduct diagrams. Errand of first conduct diagram is to watch the position of the markers. On the premise of this application the client can gather, assess and to utilize the data about general development in genuine workplace. Introduced conduct diagram gives a view on general consistent circles that are utilized for altering and examination of data from ATR catch yields. BBs called Iterator can allocate amend name of the part which ought to be connected into the virtual condition by arrange given by the legitimate circle (Paelke 2014). On account of that there are controlling guidelines accessible: parameters of definite vector, introduction and beginning vector from past advance. Organize arrangement of the marker in the genuine condition is related to the assistant framework from virtual space. Such association built up with utilized of beforehand specified components makes the platform for fundamental conceivable outcomes of augmented reality where genuine view is related and covered with the 3D condition. New facilitate framework gets the essential data from looking at segment and legitimate circle system shows the way toward moving the 3D section on its direction with parameters got from information exhibit. Every one of this information is moved in space called Loading area. Simultaneously with this procedure all data about positions are sent and allocated to the BBs called Get Position which sits tight for enactment before moving to the near segment of the conduct diagram (Aromaa and Väänänen 2016). In the area for correlation, the received data and information are considered by different BBs to process and to assess those genuine information and the virtual ones. To improve, by methods for the positional information from the marker of following framework the application can appoint the virtual facilitate framework in the focal point of marker and utilize it for showing purposes identified with virtual part development.
Cost Benefit Analysis
BBs that is taking a shot at Switch on Message guideline always screens the activity of catch reactivation. Showing segment at that point has two potential outcomes: to favor moving direction of the 3D section or to offer some incentive of the last vector position. After first catch enactment, the BBs Switch on Message gets the affirming message and vital data around 3D model is sent from the information exhibit to positional and looking at areas. Important information piece of looking at segment recalculates and assesses essential estimation of the 3D section to keep it related to the genuine framework. Facilitate affirmation inputs thusly proceed to the showing area where the last procedure of manufacturing of part is acknowledged and the costumer can see the procedure of the moving of the 3D section as per its direction (Gorecky et al. 2014). Along these lines all new data of position and introduction are sent again into the sensible areas of conduct chart with rehashed testing, examination and assessment of new coming parameters. This is rehashed until the point when the catch is reactivated. At that point the development is halted and substituted by the estimation of definite position vector acquired from information exhibit (Chi, Kang and Wang 2013). In the event that the catch is squeezed once more, the BBs Iterator sends request to move to the following line in the information cluster.
From the analysis of the two, it can be said that both the augmented reality and virtual reality technologies can be integrated into one system if the advantages of both can applied within the entire process. Virtual reality can help to prepare a product roadmap and visualize the possible design for a particular product and augmented reality can help to prepare 3D models for the proposed new products.
Conclusion
In this report, the two technologies have been discussed and a product roadmap have been created for a particular manufacturing company. VM or Virtual Manufacturing is characterized as an incorporated engineered manufacturing condition for upgrading all levels of choice and control in a manufacturing framework. VM is the joining of VR and manufacturing advances. The extent of VM can extend from a coordination of the design sub-capacities, (for example, drafting, limited component examination and prototyping) to the total capacities inside a manufacturing undertaking, for example, arranging, operations and control. Augmented reality framework gives an intricate view on dealt with territory and applicable procedures. Virtual parts are joined with genuine components. It is a common existing of client’s genuine scene together with computer’s virtual scene what is considered as a growth. These strategies for improved client condition discover its usage in numerous modern circles, for instance in range creation of parts from composite materials.
Long-Term Strategies
References
Aromaa, S. and Väänänen, K., 2016. Suitability of virtual prototypes to support human factors/ergonomics evaluation during the design. Applied ergonomics, 56, pp.11-18.
Barfield, W. ed., 2015. Fundamentals of wearable computers and augmented reality. CRC Press.
Billinghurst, M., Clark, A. and Lee, G., 2015. A survey of augmented reality. Foundations and Trends® in Human–Computer Interaction, 8(2-3), pp.73-272.
Büttner, S., Mucha, H., Funk, M., Kosch, T., Aehnelt, M., Robert, S. and Röcker, C., 2017, June. The design space of augmented and virtual reality applications for assistive environments in manufacturing: a visual approach. In Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments (pp. 433-440). ACM.
Chi, H.L., Kang, S.C. and Wang, X., 2013. Research trends and opportunities of augmented reality applications in architecture, engineering, and construction. Automation in construction, 33, pp.116-122.
Engelke, T., Keil, J., Rojtberg, P., Wientapper, F., Schmitt, M. and Bockholt, U., 2015, March. Content first: a concept for industrial augmented reality maintenance applications using mobile devices. In Proceedings of the 6th ACM Multimedia Systems Conference(pp. 105-111). ACM.
Gorecky, D., Schmitt, M., Loskyll, M. and Zühlke, D., 2014, July. Human-machine-interaction in the industry 4.0 era. In Industrial Informatics (INDIN), 2014 12th IEEE International Conference on(pp. 289-294). IEEE.
Makris, S., Karagiannis, P., Koukas, S. and Matthaiakis, A.S., 2016. Augmented reality system for operator support in human–robot collaborative assembly. CIRP Annals-Manufacturing Technology, 65(1), pp.61-64.
Nee, A.Y. and Ong, S.K., 2013. Virtual and augmented reality applications in manufacturing. IFAC Proceedings Volumes, 46(9), pp.15-26.
Ong, S.K. and Nee, A.Y.C., 2013. Virtual and augmented reality applications in manufacturing. Springer Science & Business Media.
Paelke, V., 2014, September. Augmented reality in the smart factory: Supporting workers in an industry 4.0. environment. In Emerging Technology and Factory Automation (ETFA), 2014 IEEE(pp. 1-4). IEEE.
Posada, J., Toro, C., Barandiaran, I., Oyarzun, D., Stricker, D., de Amicis, R., Pinto, E.B., Eisert, P., Döllner, J. and Vallarino, I., 2015. Visual computing as a key enabling technology for industrie 4.0 and industrial internet. IEEE computer graphics and applications, 35(2), pp.26-40.
Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P. and Harnisch, M., 2015. Industry 4.0: The future of productivity and growth in manufacturing industries. Boston Consulting Group, 9.
Wang, X., Truijens, M., Hou, L., Wang, Y. and Zhou, Y., 2014. Integrating Augmented Reality with Building Information Modeling: Onsite construction process controlling for liquefied natural gas industry. Automation in Construction, 40, pp.96-105.
Wei, X., Weng, D., Liu, Y. and Wang, Y., 2015. Teaching based on augmented reality for a technical creative design course. Computers & Education, 81, pp.221-234.
Westerfield, G., Mitrovic, A. and Billinghurst, M., 2015. Intelligent augmented reality training for motherboard assembly. International Journal of Artificial Intelligence in Education, 25(1), pp.157-172.