Abstract
Renewable sources of energy play a decisive role in the current energetic paradigm to mitigate climate changes associated with greenhouse gases emissions and problems of energy security. Biomass energy and in particular forest wood biomass supply chains have the potential to enhance these changes due to its several benefits such as ability to produce both bioenergy and bioproducts, generate energy on-demand, among others. However, this energy source has some drawbacks mainly associated with the involved costs. In this work, the use of a Model Predictive Control approach is proposed to plan, monitor and control the wood-biomass supply chain for energy production at a tactical level. With this methodology the biomass supply chain becomes more efficient ensuring the service quality in a more competitive way. In order to test and validate the proposed approach different simulation scenarios were considered that proved the efficiency of the proposed tool regarding the decisions definition and control.

Abstract
This paper demonstrates the potential benefits of the integration of robot based sensing and Enterprise Information Systems extended with information about the geometric location and volumetric information of the parts contained in logistic supermarkets. The comparison of this extended world model with hierarchical spatial representations produced by a fleet of robots traversing the logistic supermarket corridors enables the continuous assessment of inconsistencies between reality, i.e., the spatial representations collected from online 3D data, and the modelled information, i.e., the world model. Results show that it is possible to detect inconsistencies reliably and in real time. The proposed approach contributes to the development of more robust and effective Enterprise Information Systems.

Abstract
This paper presents a framework to support the full life-cycle of extended manufacturing enterprises, from creation to operation and dissolution phases. The deployment and operation of such enterprises can be compared with the concept of 'plug-and-play', as the internal processes and legacy systems of the companies involved are smoothly integrated within an overall business process designed, validated and executed according to a specific business opportunity. During the plug phase, the specific business requirements are elicited and integrated with the design of the extended business processes. On the other hand, in the play phase, those predefined processes are executed in order to run the extended enterprise successfully. The paper describes an application case regarding an engineer-to-order and one-of-a-kind engineering product. This scenario is common to a large number of technology-driven SMEs, and illustrates the value of the framework to exploit business opportunities that require a combination of skills and resources that do not exist in-house. The case shows how the platform addresses the two main challenges in the deployment of an extended enterprise. The first challenge is finding the right set of partners to address a new business opportunity and the design of the underlying collaborative processes. The second challenge is mostly technical, and focuses on the integration of the legacy systems of the partners participating in the network so that cooperation can take place quickly and seamlessly.

Abstract
Tactical production-distribution "planning models have attracted a great deal of attention in the past decades. In these models, production and distribution decisions are considered simultaneously such that the combined plans are more advantageous than the plans resolved in a hierarchical planning process. We consider a two-stage production process, where in the first stage raw materials are transformed into continuous resources that feed the discrete production of end products in the second stage. Moreover, the setup times and costs of resources depend on the sequence in which they are processed in the first stage. The minimum scheduling unit is the product family which consists of products sharing common resources and manufacturing processes. Based on different mathematical modelling approaches to the production in the first stage, we develop a sequence-oriented formulation and a product-oriented formulation, and propose decomposition-based heuristics to solve this problem efficiently. By considering these dependencies arising in practical production processes, our model can be applied to various industrial cases, such as the beverage industry or the steel industry. Computation tests on instances from an industrial application are provided at the end of the paper.

Abstract
Cognitive robots have started to find their way into manufacturing halls. However, the full potential of these robots can only be exploited through an integration into the automation pyramid so that the system is able to communicate with the manufacturing execution system (MES). Integrating the robot with the MES allows the robot to get access to manufacturing environment and process data so that it can perform its task without human intervention. This paper describe the mobile robotic manipulator developed in the EU project STAMINA, its has been integrated with an existing MES and its application in a kitting task from the automotive industry.

Abstract
This paper presents an integrated cognitive robotics system for industrial kitting operations in a modern factory setting. The robot system combines low-level robot control and execution monitoring with automated mission and task planning, and a logistics planner which communicates with the factory's manufacturing execution system. The system has been implemented and tested on a series of automotive kitting problems, where collections of parts are picked from a warehouse and delivered to the production line. The system has been empirically evaluated and the complete framework shown to be successful at assembling kits in a small factory environment.