Product developers are faced with the challenge of covering an ever-increasing external variety with as little internal variety as possible. Modular product architectures offer one way of resolving the challenge. They have an impact on all life phases and on economic targets. These effects are represented in the Impact Model of Modular Product Families. A large number of modularization methods can be found in the literature. The modularization methods consist of different activities: decomposition of product, analysis and revision of components and reintegration to modules. Module drivers play a major role in reintegration, as they determine which components together form a module. It is not yet clear what effects different modularization methods involving different module drivers have on economic targets. For this reason, the module drivers are examined in their role as levers of modularity and integrated into the Impact Model via access points. By documenting the results in a specially developed uniform method step description and in the Impact Model, we enable the selection of modularization methods with regard to their economic impact. The introduction is followed by the state of research. In section 3, the research problem and the research approach are presented. In section 4, the generic method-step description is applied to seven modularization methods. Based thereon, the modularization methods are compared with each other with regard to their addressed economic objectives. In an explanatory example, the method selection made possible by this is presented. Finally, the results are discussed and an outlook is given.

The use of product-service systems business models is increasing in today's economy. Because the products that provide the service to the customers incur cost during their lifetime, the method of lifecycle costing finds wide-spread use. However, this paper shows the current methods have some inaccuracies when determining lifecycle costs. The methods do not consider the required number of products necessary to provide the offered service to the customers. This paper describes a new framework for lifecycle costing that includes these cost components.

By transforming from a manufacturer into a PSS provider, the business model of a company changes. In particular with service-oriented business models, the importance of tangible products alters. Instead of selling products, PSS providers need product fleets that enable the provision of services. If the manufacturer of the product and the provider of the PSS fleet are identical, the products can be designed specifically for the PSS. This paper introduces a framework that supports the design of modular PSS fleets so that the product architecture is optimised for the requirements of the fleet.

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With the spread of product-service systems as business models the life cycle costs are of increasing importance as a measurement of product cost. A key factor that drives these costs is the desired reliability of the products used to provide the service. Since the customer usually expects as uninterrupted service availability, it is imperative to achieve the the required reliability. Therefore a large variety of methods has been developed to maximize the reliability of a product. But these approaches focus on the maximization of the reliability and disregard the resulting product costs. This can lead to designs that over perform concerning their reliability requirements but also exceed their target costs. Which will result in the product-service system not being competitive in the marketplace or lowering the company's profit. This paper shows an approach on how to use markov chains to enable a quick comparison of life cycle costs from different product-service system designs With this it will be possible to make better informed decisions about the costs of a system while still meeting the reliability targets.