In today's highly competitive industries, engineers are driven to not only design a better product to fulfill users' needs but also demanded to develop a product in a short time to occupy the market. With the development of data collection and visualization technology, the application of data visualization into product development to enhance the ability of better product design is a significant trend.  Data visualization becomes more and more important since it could illustrate the valuable information, such as tacit needs and patterns which hidden from data, in a communicated way to help engineers get more inspiration for the conceptual design.   It is not hard to collect data; however, the challenge is to visualize the valuable information from a large number of data concisely and intuitively. In recent years, there are some visualization techniques available for product design, while, most of them are implemented in the later stage of product development, few methods are applicable for conceptual design. Therefore, this thesis is carried out to explore appropriate visualization techniques to provide support for conceptual design.   The aim of this thesis is, in an engineering environment, to investigate ways to visualize complex data legibly and intuitively to enhance engineers’ ability for conceptual design from better understanding the current machine. In order to achieve the objective, a conceptual design case of the improvement of wheel loader fuel consumption is applied, which consisted of plenty of data sets within various parameters, to explore how to reveal the hidden information of complex data for engineers.   As the result of this thesis, a prototype contains a series of visualization techniques is proposed to demonstrate data information from a wheel loader under several visualization situations. The final prototype has the functions of visualizing different operations separately; visualizing the overall fuel consumption in one operation; cluster's patterns visualization; visualizing the impact of one variable on the whole value.