Digital Manufacturing and Design Innovation †MyAssignmenthelp.com

Question: Discuss about the Digital Manufacturing and Design Innovation. Answer: Introduction: After analyzing the business processes it has been found that, for the adaptation of beneficial office automation system SoftArc engineering company is dependent upon both cloud computing technology and big data analytical tools (Abolfazli et al., 2014). The overall capability to access office automation system in terms of email, word processing and spreadsheet ability, this technology is found to be very much helpful. However, if the technologies are not used appropriately then the overall system will lead to major failure. This report elaborates both the issues and benefits of business intelligence and cloud computing technology. Elasticity: The cloud vendor provides high range of storage location and also innumerous amount of demand based resources to its users. Even for the future resource requirements also the users need not to spend much time (Furuncu Sogukpinar, 2015). Depending on the requirement the users can scale up or scale down the resources. Moreover, the consumers can also redeploy the overall expenditure form the capital and for commercial benefits these technology can also be used. Accessibility: From the storage the users can efficiently access data regardless of their location and time also. Even, with the help of the multiple interfaces the user can effectively access the virtual data server. Due to this reason the workstation of the employees can also varies. Cost efficiency: The consumers have the ability to share different computing resources. The cost efficiency of the consumers can be easily forwarded, based on the demand of the consumers. Application resilience, disaster recovery and backup: The cloud data server has three different kinds of features such as application resilience, backup storage and disaster recovery. If any information from the server gets lost then that can be easily retrieved and recovered as well (Abolfazli et al., 2014). With the help of this technology the overall effectiveness of the system also get increased. Issues with bandwidth: In order to perform effectively the clients of the system are required to develop system planning properly (Almorsy, Grundy Muller, 2016). Bandwidth oriented issues will rise if small data centre are used for storing information. Control issues: For the in-house staffs the service cannot be handled properly. Issues with change management: If the cloud platform gets changed suddenly then, the staffs will not be able to handle the technology appropriately. Business Intelligence oriented issues and benefits Benefits: In order to take effective business strategic decisions business intelligence tools are very much helpful. Not only this but also the knowledge could be converted into information after the usage of the business intelligence. Nowadays the most widely used BI tool is Hadoop (Jamshidi, Ahmad Pahl, 2014). Challenges: If the data amount overflows the server capability then the process of data integrity will be hampered. In addition to this if the employees lack proper BI based experiences then they will not be able to handle the system properly. Lack of security is another issue that might destroy the complete system management. After analyzing both of the technical advances from the business aspect it has been found that for SoftArc Engineering the best possible solution is to use cloud computing technology. Cloud technology will help to increase the business revenue of softArc Engineering (Bacon et al., 2014). After adapting this technology the users will be able to access data from the office automation system. Factors locally hosted infrastructures Infrastructure provided using an IaaS provider Security It serve high range security to the users The shared data are not enough secured Cost The cost is lesser than other applications This infrastructure is too costly Data accessibility Limited data could be accessed (Almorsy, Grundy Mller, 2016) No limitation Issue mitigation strategies considered by SoftArc Engineering Vendor lock-in: Dependency on the cloud service provider is the vendor lock in system. The main challenge occurs if after implementation the owner feels to change to platform. Security: Security is referred to as one of the major concerns for the cloud computing technology (Hashem et al., 2015). For mitigating this issue the users are required to select appropriate cloud vendors with accurate authentication approach. Vulnerability: Prominent risk will rise if the users need to change the platform suddenly. Due to the system dependency the rate of malicious attack will also raise and even for this reason confidential data might also get hijacked by the external attackers (Jamshidi, Ahmad Pahl, 2014). IaaS PaaS SaaS Multiple numb of users are able to share the single hardware system The system is build upon top level virtualization technology (Kar Rakshit, 2015). In the remote server this particular software can be hosted. It provides measurable control over the system and it has high level flexibility and reliability. It is capable to serve different range of service to the users for facilitate various development programs, testing and software application as well. The application of SaaS can be managed from the centralized location. Due to the dynamic scaling ability the cost of the infrastructure also varies (Wu et al., 2015. Integrated web and data services could be served by this particular cloud provider. With the help of Application Programming Interfaces (API) even third party can be integrated. Appropriate cloud model selection for SoftArc Engineering After analyzing the features of different cloud computing model it has been found that, one of the most suitable model for SoftArc Engineering is IaaS. This platform is capable to establish connection between different users who are belonging from discriminated platforms. This model is appropriate for the business organization due to its measurable control over the performing applications (Kehoe et al., 2013). Apart from SoftArc Engineering this model is also suitable for the startup businesses. The volatile demand of the consumers can also be served efficiently by adapting this model as the organization is willing to move to SharePoint 2013. Security: During the phase of platform migration the main issue that has been encountered is the security. On demand infrastructure capability: With the enhancing usage of mobile devices that is merged with on demand virtual infrastructure, major challenges with cloud model can be generated (Sundaresan et al., 2016). System dependency: The IaaS cloud model is one of the most dependent models and whenever different programs ran over a single platform, ongoing concern is required to be provided. Recommendations to SoftArc Engineering to deal with the identified issues In order to deal with the identified issues, different issue mitigation strategies are required to be adapted by the system developers. Incorporation of security: In order to mitigate the identified challenges proper security measures are required to be adapted by the system developers to maintain the server security. Authentication: This is another system approach that is needed to be considered to make a system authorized. With the authentication approach only the authorized users will be able to access data from the server. From the data management system only the users will be able to maintain the standard privacy policy. Technology based development: The storage system of SoftArc Engineering is needed to be technically developed to deliver high level security to the users and employees as well. References Abolfazli, S., Sanaei, Z., Ahmed, E., Gani, A., Buyya, R. (2014). Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges.IEEE Communications Surveys Tutorials,16(1), 337-368. Almorsy, M., Grundy, J., Mller, I. (2016). An analysis of the cloud computing security problem.arXiv preprint arXiv:1609.01107. Bacon, J., Eyers, D., Pasquier, T. F. M., Singh, J., Papagiannis, I., Pietzuch, P. (2014). Information flow control for secure cloud computing.IEEE Transactions on Network and Service Management,11(1), 76-89. Furuncu, E., Sogukpinar, I. (2015). Scalable risk assessment method for cloud computing using game theory (CCRAM).Computer Standards Interfaces,38, 44-50. Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., Khan, S. U. (2015). The rise of big data on cloud computing: Review and open research issues.Information Systems,47, 98-115. Jamshidi, P., Ahmad, A. Pahl, C., (2014), June. Autonomic resource provisioning for cloud-based software. InProceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems(pp. 95-104). ACM. Kar, A.K. Rakshit, A., (2015). Flexible pricing models for cloud computing based on group decision making under consensus.Global Journal of Flexible Systems Management,16(2), pp.191-204. Kehoe, B., Matsukawa, A., Candido, S., Kuffner, J., Goldberg, K. (2013, May). Cloud-based robot grasping with the google object recognition engine. InRobotics and Automation (ICRA), 2013 IEEE International Conference on(pp. 4263-4270). IEEE. Sundaresan, K., Arslan, M.Y., Singh, S., Rangarajan, S. Krishnamurthy, S.V., (2016). FluidNet: a flexible cloud-based radio access network for small cells.IEEE/ACM Transactions on Networking,24(2), pp.915-928. Wu, D., Rosen, D. W., Wang, L., Schaefer, D. (2015). Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation.Computer-Aided Design,59, 1-14.