Apollo Hospital Patient Database Upgrade

The purpose of this project to centralize, standardize, unify the Apollo Hospital’s patient management database across all locations. This will allow for reduced overhead and conflicts due to patient scheduling, patient records review/requests, and information sharing. This will result in a more efficient, streamlined, and error-free experience for our patients and our staff

Site Selection Evaluation utilizing HDM Model & STEEP Perspectives: Case Study - Pyramid Power

This paper presents a limited framework using Hierarchical Decision Making model with STEEP perspectives to assist in site selection for an environmentally focused waste energy conversion project. The framework in limited in that the structure presented is a stem, the beginning, and should be expanded upon if used. Examples of expansion criteria are given in this document to be considered along with relevant criteria derived from specific company and project background. When choosing where to implement an energy-sector green project on a global scale there are countless factors that can help a project succeed or fail. Literature research yielded consistent and historical vetted cases where STEEP (social, technical, environmental, economic, political - sometimes abbreviated to PEST or PESTEL) perspectives were proven effective. This paper presents a model where project locations can be plugged in and relative weights can easily be assigned to suggest and categorize locations. To prove the model, a sample case study was used against the limited model for the company Pyramid Power in an endeavor to select a location for industrial diesel generator heat capture tooling. This tooling improves energy output by as much as 30% without additional fuel. The scale and success of this initial project are crucial to the success of the company, thus site selection is a top priority

Employee Training Schedule Optimization

As the amount of technical information explodes in volume and technical professionals struggle with staying current with the latest information, one important channel is the large scale trade or technical conference. Bringing value back to business by keeping employees up to date with trends in the industry is something that a company expects when it invests time and money in sending its employees to such conferences. To choose sessions from a large conference is an exacting job for employees as they need to scroll over such huge data set and select the best session that matches their interest and preferences. This results in large number of employee hours consumed, which ultimately can prove expensive to a company. Due to these reasons, organizations might find formal planning methods beneficial to get the best return on their investment. To test this, we are examining the case of a major automotive industry company named Daimler Trucks North America. This company is sending six of its employees from the IT department to attend a conference conducted by IBM called “World of Watson”. Human Resource and IT capability being key resources to create competition and differentiating factors between two companies. Training presents a prime opportunity to expand the knowledge base of all employees, but companies and employees alike find this activity a little taxing, what with training conferences having a rigid schedule, with back to back sessions, some even running parallel to each other and add to this the work schedule of employees and their varying skills level and interests, companies and employees face variety of issues to be sorted out before employees can actually figure out which session to attend. The main objective of this project is to take the interest of the employee into account and develop an optimized schedule for 6 Daimler employees who have to attend a three-day training conference being organized by IBM. The primary metrics used for this schedule planning are the availability of employee, their skill level, and the area of preference. To increase overall coverage of sessions, we came up with a model that does not assign the same session to two employees. The model also assures that no time slot is left vacant. This helped with increasing the scope of learning. Currently, Daimler has a traditional and delegated approach, where another employee was given the task of going through the list of sessions and to choose the sessions each attendee should attend. The main problem with this approach is that the entire decision of selecting sessions is manual and hence not very personalized. This paper attempts to propose a scheduling tool based on excel to cope with the complex task of picking the best session to be attended by an employee based on their pillar preferences

Marketing Plan for June Smart Oven

In this technological era, there is a huge market of smart appliances industry. Smart kitchen appliances are the subset of the overall smart appliances industry. The most significant factors which fuels the smart kitchen appliances growth are increasing advancements in the home appliances sector. The market is also complemented by the growing smart grid market. Smart kitchen appliances are among the most important components of the smart grid ecosystem since it enables two-way communication