Abstract
Purpose - The purpose of this paper is to study the alignment measurement in collaborative networks, using the fit concept and predictive performance measurement as its main enablers. A performance prediction approach is used in order to control a collaborative business network based not only in present and past performance measurements of each partner, but also taking into account the future behaviour of the intra- and inter-organisational processes performance. Design/methodology/approach - An exploratory case study was applied to a Brazilian collaborative network and mathematical approaches normally used in control theory were adopted to support alignment measurement. Findings - The use of predictive measurements to manage the alignment between the results of inter-organisational processes and performance targets set by the collaborative network. Research limitations/implications - This approach was applied in a specific supply chain network, based on three industrial companies. For other network typologies it will be necessary to evaluate the alignment that can be achieved. Practical implications - This predictive approach makes it possible to manage performance pro-actively using feedforward and feedback control. Therefore, tools that consider performance estimation are used based on a data fusion approach, with a proper combination of leading and lagging measurements, which make it possible to use forecasting methods and tools to achieve good predictions. Originality/value - The paper introduces an approach to alignment measurement leveraged by the new paradigm of performance prediction and presents an alignment metric for collaborative networks. © Emerald Group Publishing Limited.

Abstract
In order to develop the new industrial paradigm, it is necessary to explore a framework supported by planning and operational tools. Indeed, it becomes clear that more and more the next factories need to be increasingly more flexible, agile and knowledge-based in order to be able to adapt in real time to the continuously changing market demands, technology options and regulations, as well as accelerate the design process and optimise production. Therefore, in this paper a framework capable of supporting the factory planning will be presented based on predefined templates and product requirements. Furthermore, the Factory Templates will allow for process deployment, control and evaluation in real-time. © 2011 AISTI.

Abstract
The manufacturing industry faces a new revolution, grounded on the intense digitalization of assets and industrial processes and the increasing computation capabilities imposed by the new data-driven digital architectures. This reality has been promoting the Digital Twin concept and its importance in the industrial companies' business models. However, with these new opportunities, also new threads may rise, mainly related to industrial data protection and sovereignty. Therefore, this research paper will demonstrate the International Data Spaces reference model's application to overcome these limitations. Following a pilot study with a Portuguese machine producer/maintainer enterprise, this paper will demonstrate the development of a cutting and bending machine Digital Twin, leveraged on an International Data Spaces infrastructure for interoperability, for the plastic and metal industry and its importance to introduce this machine manufacturing company in a new business-to-business marketplace from the EU project Market 4.0.

Abstract
Recently, we have been observing a significant evolution in products, machines, and manufacturing processes, towards a more digital and interoperable reality. In this sense, the power transformers sector has also been evolving to develop smart transformers for the future, capable of providing the digital capabilities to leverage new services and features that follow its entire life cycle, from the design and manufacturing to the use and dismantling/recycling. In this sense, this paper aims to present and demonstrate how an innovative digital twin platform can be used in a secure and trustable way for the enhancement of the power transformers’ performance and potential lifespan, enabling, at the same time, the promotion of new business models. A real use case is also presented to demonstrate the applicability of Asset Administration Shells (AAS) for power transformer life cycle management, as well as the use of the International Data Spaces (IDS) for the secure and trustable horizontal interoperability along with the different actors of the value chain, from the manufacturers to the power network and maintenance services companies.