Digital Product Innovation in Manufacturing Industries

TARGET GROUP: MANUFACTURING INDUSTRIES

OBJECTIVES

·        To develop a comprehensive model describing to organize and structure abundant and diverse opportunities seems analytically useful for product developers and decision makers discovering the benefits of digitized products.

·        To identify the extent of augmentation of traditional physical products with digital components.

SUMMARY

Managing the lifecycle of industrial products has been perceived as a challenging issue in both academia and industry for several decades. Within the setting of manufacturing, an established conceptualization of this product lifecycle is the division into beginning-of-life (BOL), middle-of-life (MOL), and end-of-life (EOL). Thereby, BOL encompasses product conceptualization, definition, and realization. MOL comprises product usage, service, and maintenance. EOL may be shaped by various pathways ranging from refurbishing to disposal. From a chronological viewpoint, these phases are commonly not distributed equally. Dependent on the product type, the duration of the MOL phase can exceed the duration of the BOL phase by far. On closer examination, industrial enterprises have very limited information about the actual usage of their products once they are sold to their customers. Although it is widely acknowledged that information about product usage is highly beneficial for the development of future products, manufacturers scarcely get feedback from the field – with the exception of selective snapshots from customer service or even complaints from customers. Conditioned by lacking technological capabilities, product usage has received little attention from product development departments in the past. However, in the light of pervasive digitalization, traditional physical products get augmented with digital components that create the potential of making the whole product lifecycle visible for product developers. Traditional industrial products ranging from heavy engineer-to-order machinery to automotive make-to-stock-planning modules get infused with digital technologies such as sensors, networks, and processors.

REFERENCE

https://scholarspace.manoa.hawaii.edu/items/908d711b-c634-4c60-a5b1-4ebce7a9d7bb