Technology road-mapping is a significant method to help companies gain orientation concerning future challenges. This work contains a description of technology road-mapping in four major parts, providing expert knowledge on framing/embedding of technology road-mapping, processes of technology road-mapping, implementing technology road-mapping and linking technology road-mapping to other instruments of strategic planning. Technology Roadmaps aligns the development of their products and their supporting technologies. These roadmaps aligns investments in technology and develop new capabilities, so that they are able to make capitalize on the future market direction and stay ahead of the curve in terms of technological evolution. This bridges the relationship between technologies and an enterprises' products and services. As a result, an enterprise's technological status can be maintained or improved.
Roadmaps can have different applications such as :
There are different kinds of Roadmaps; nevertheless, our focus on the design of Innovation/transformational Roadmaps. The objective is to provide a strategy an enterprise will have to evolve related products/services and the supporting technologies. These transformational roadmaps will have to consider various factors of Organizational change management, current technological foot print, capability and investments.
The Roadmap shows the most relevant technologies that permit the development of the analyzed object, while taking time into account. For this analysis, technologies must be taken into account, especially the ones available within the Roadmap's time scope. Accordingly, future developmental approaches must be established for three technological categories:
In addition, dynamics of technology development, like technologies’ life cycles, must be taken into account. Particularly, relevant tendencies of the market as well as the tendencies of consumers’ needs are dynamics that can deeply influence the rhythm of development of these technologies.
Take measurements of work-in-progress products to find manufacturing defects as early as possible, while also identifying any potential process or design flaws. Since defects are typically the result of many factors, analyzing long histories of assembly line sensor data can find subtle anomalies that signify product flaws. Apache Hadoop stores long histories of sensor data while also enabling high speed, real-time, early-warning analytics that correlate real-time measurements with other disparate data, then compare to quality models.
Minimize Non-Productive Time (NPT) by monitoring equipment or product utilization in a live environment to identify patterns that indicate imminent failure. For revenue-generating operations equipment, downtime results in significant lost revenue as well as costly repairs. MapR Distribution for Hadoop enables ongoing analysis of an entire system and lets businesses predict when failure might occur, so preventive maintenance can avoid the failure. For consumer products, failures or need for replacement will depend highly on usage patterns, and tracking those patterns help manufacturers to alert customers when their products need specific maintenance.
Track the movement of vehicles and products to identify the costs of various transportation and process options. By using Hadoop to analyze large volumes of historical, time-stamped location data, businesses can calculate optimal delivery routes and enable dynamic rerouting to minimize the impact of arbitrary obstacles like traffic, energy prices and weather. Businesses can also leverage the optimal delivery system as a revenue-generating basis for premium/expedited delivery services to consumers.
Once a product is manufactured and shipped, companies may have little information on its performance. In order to be able to predict potential product component failures, companies leverage MapR Distribution for Apache Hadoop to combine reading from advanced sensors, data feeds from consumer devices, and use Apache Mahout and other analytic methods and libraries to predict the time and cause of future failures.