Petter Kyösti

A model for predicting and monitoring industrial system availability

This paper describes the integration of a sensor data stream monitoring system into a proposed functional product model capable of predicting functional availability. Such monitoring systems enable ...

Evaluating availability of functional products through simulation

Abstract A functional product is an integrated package consisting of hardware, software and a service support system that provides a customer with a certain function and is sold under a performance-based contract that includes a functional availability guarantee. For the availability performance, prediction, optimisation and management of risk are therefore important concerns during product development. This paper describes a software tool that can generate an integrated model of a functional product from its design details and analyse it through simulation to provide availability performance information. The model’s application to the analysis of a real industrial system is demonstrated. Such tools are important for the development and widespread adoption of functional products. The resulting analysis gave an indication of a suitable guaranteed functional availability level for the product and could be used to compare the performance of different design options.

Prediction of service support costs for functional products

Abstract In the functional product business model, a customer is provided with functionality at a guaranteed level of availability under a pre-agreed pricing structure whilst the provider retains ownership of the hardware and provides a service support system to deliver services such as maintenance. The ability to accurately predict the costs of supporting functional product contracts is crucial to the provider in correctly pricing those contracts and for the development and implementation of an efficient service support system. Since the costs incurred are performance based and accumulated over a long duration, they are difficult to predict without effective modelling and decision support tools. This paper discusses a decision support tool that has been developed to provide detailed analysis of the predicted long-term costs of supporting functional product contracts. The tool features a web based user interface to allow collaborative use of the tool by multiple users. The cost predictions are obtained through a discrete event simulation model that emulates the performance of the hardware and service support system used by the provider to fulfil the functional requirements specified in the contracts. The simulations are executed on automatically provisioned remote web based servers, meaning that the computing resources utilised are not limited by the user’s client device. The tool is demonstrated via application to an industrial test case.

Development and Operation of Functional Products: Improving Knowledge on Availability Through Use of Monitoring and Service-Related Data

The book chapter addresses which measures five manufacturing companies have taken, or plan to take, regarding use of data originating from monitoring, service, support, maintenance, repairs as well as other sources, in order to improve the knowledge on availability in the context of providing Functional Products. Commonly, the objective of Functional Products is to provide a function to customers with a specified level of availability (or improvement of productivity or efficiency). The results indicate that systematic planning and collection of relevant data, which is either pre-processed on-board (i.e., locally) or sent as is to central or cloud-based storage and processing, in combination with additional necessary data from other sources, is crucial to build knowledge in order to uphold and improve the level of availability agreed upon with customers. As the use of software in Functional Products increases, the knowledge on availability related to software must be augmented—which can be a challenge for many companies whose operations have been rooted in hardware. Further, the results reveal that getting high-quality input is key in order to use the collected data for analytics and to find root causes. The latter may change how the current value-chain operates and secures the quality of necessary data when providing functions to customers if partners are involved in the provider consortium.