Quality Function Deployment (QFD) has been traditionally used as a planning tool primarily for product development and quality improvement. In this context, many people have used QFD for making Decisions on how to prioritize critical product areas from a customer perspective.However, it is the position of the author that the QFD process can be viewed as a Decision Support System that would encompass multiple facets of information to enhance the quality and output of the Decision making process in the course of product development. In this paper, the author submits the QFD process in combination with other engineering Decision making tools such as the Pugh concept selection and the Kepner-Tregoe analysis technique as a Decision making and modeling process that is as old as management science itself. Specifically, the attempt is made to illustrate how QFD provides an iterative sequence of steps involved in Decision making, from the initial problem identification to a proposal for the actual implementation plan. To make this position more applicable to the reader, the subject has been approached from an actual business environment.

The Trips selection will become even more important nowadays especially as online trips in large trips databases can be used to give online travelers a better choice of trips than can be found off-line.The process of selecting a trip is considered as one of the most difficult stages a traveler goes through, especially with tens of trips of similar goals, different prices and detailed characteristics in the market.This paper is interested in proposing a Decision Support System to select the optimal Trip that meets each traveler's preferences; using Case- Based Reasoning techniques ' CBR', and calculating similarity between the traveler's preferences and the trip characteristics.

In recent years, the Internet of Things (IoT) brings a new dimension for establishing a precision network connectivity of sensors, especially in the agriculture and farming industry, medical, economic, and several sectors of modern society. Agriculture is an important area for the sustainability of mankind engulfing manufacturing, security, and resource management. Due to the exponential diminishing of the resources, innovative techniques to Support the subsistence of agriculture and farming. IoT aims to extend the use of internet technology to a large number of distributed and connected devices by representing standard and interoperable communication protocols. This paper brings up a solution by IoT, presents the design and implementation of a smart pre-seeding Decision Support System for agricultural modernization. This project is accomplished by understanding the real-time circumstances in the agriculture field using wireless technology that highlighted the features including pH and temperature sensors, hardware, mobile application, System’ s frontend, and backend analysis, and stores the extracted information in the cloud using IoT. The System is made up of frontend data acquisition, data transmission, data processing, and reception, and is also experimentally validated to find out all possible crops that can be cultivated in a specific land with the required amount of fertilizers as well as the overall crops distribution lists.

Providing a plan for any corporate or firm at macro level, as an organization or enterprise resource planning has particular importance nowadays. To meet the enterprise resource planning needs applications software packages provide a set of uniform pre-prepared and pre-designed that covers all business process throughout an organization. To achieve maximum efficiency in the implementation of these packages and their synchronization with the needs, organizations face a very complex problem. In this paper, a Decision Support System to be used for planning in various economic firms is presented. By using this System, the managers can investigate their corporate in the past and then they can make a plan for future. We implemented the proposed Decision Support System for a company in Iran. This company has two production lines subject to exchange rates. In the evaluation, four alternatives to make the plan for future are applied. The experimental results show the optimizing the exchange rate allocated to production lines provides the best solution for this company.