Abstract
Today, manufacturing is moving towards customer-driven and knowledge-based proactive production. Shorter product life cycles lead to increased complexity in areas such as product and process design, factory deployment and production operations. To handle this complexity, new knowledge-based methods and technologies are needed to model, simulate, optimize and monitor manufacturing systems. Product lifecycle management research tends to focus on situations that are responsive to formal analysis and modelling. However, in several domains such as knowledge intensive collaborative environments, it's not possible to model processes using formal notations. Knowledge based and collaborative process management involves a combination of structured and non-structured processes. Structured processes management can be reduced to a set of fully-defined rules leading to high efficiency but also low flexibility, whereas the management of non-structured processes is not prone to a full formalization. A combination of both structured and unstructured management approaches is required in order to achieve a successful trade-off between efficiency, flexibility and controllability. We call a process as semi-structured when it contains both structured and non-structured sub-processes leading to a flexible and efficient hybrid approach. Large enterprise information systems, impose structured and predictable workflows, while knowledge based collaborative processes are unpredictable to some extent, involving high amount of human-decision. Moreover, large enterprise information systems are not able to manage the daily ad hoc communication inherent to the knowledge-based process itself. This paper introduces a set of concepts, methods and tools of an innovative Hybrid Process Management approach validated by a real world business case in the automotive industry.

Abstract
Forest biomass has gained increasing interest in the recent years as a renewable source of energy in the context of climate changes and continuous rising of fossil fuels prices. However, due to its characteristics such as seasonality, low density, and high cost, the biomass supply chain needs further optimization to become more competitive in the current energetic market. In this sense and taking into consideration the fact that the transportation is the process that accounts for the higher parcel in the biomass supply chain costs, this work proposes a multilayer model predictive control based strategy to improve the performance of this process at the operational level. The proposed strategy aims to improve the overall supply chain performance by forecasting the system evolution using behavioural dynamic models. In this way, it is possible to react beforehand and avoid expensive impacts in the tasks execution. The methodology is composed of two interconnected levels that closely monitor the system state update, in the operational level, and delineate a new routing and scheduling plan in case of an expected deviation from the original one. By applying this approach to an experimental case study, the concept of the proposed methodology was proven. This novel strategy enables the online scheduling of the supply chain transport operation using a predictive approach.

Abstract
Allocation of jobs to machines and subsequent sequencing each machine is known as job scheduling problem. Classically, both operations are done in a centralized and static/offline structure, considering some assumptions about the jobs and machining environment. Today, with the advent of Industry 4.0, the need to incorporate real-time data in the scheduling decision process is clear and facilitated. Recently, several studies have been conducted on the collection and application of distributed data in real-time of operations, e.g., job scheduling and control. In practice, pure distribution and decentralization is not yet fully realizable because of e.g., transformation complexity and classical resistance to change. This paper studies a combination of decentralized sequencing and central optimum allocation in a lithography job-shop problem. It compares the level of applicability of two decentralized algorithms against the central scheduling. The results show better relative performance of sequencing in stochastic cases. © IFIP International Federation for Information Processing 2017.

Abstract
Purpose - This paper aims to study and explore the activities and the use of institutional network resources by industrial business associations (IBAs) to support and facilitate internationalisation processes of small-and medium-sized enterprises (SMEs). Other goals are to understand the internationalisation follow-up process and the future vision of IBAs to improve this internationalisation support. Design/methodology/approach - Based on empirical evidence and following an abductive approach, this paper presents a qualitative exploratory field research, providing insights from interviews performed with 20 IBAs based in Portugal. Findings - The findings suggest that the current institutional network support to internationalisation is mainly provided through promotional activities; counselling, training and technical and legal support; information sharing; and cooperation with other institutional entities. Each support category is explored and explained and a new conceptual model is developed to represent these findings. Regarding the internationalisation follow-up, IBAs provide a continuous support for the international operations by using some instruments and mechanisms to assist SMEs after an internationalisation initiative. Finally, collaboration and the use of new information technology are the main aspects to improve IBAs' support in a near future. Research limitations/implications - The qualitative methodological approach adopted in this work can imply a larger difficulty to obtain a generalisation of the findings. Another limitation is that the participating IBAs are based in only one country. Practical implications - Findings can help SMEs to understand the functioning and the benefits of using the institutional network resources of IBAs in overcoming their lack of resources to operate in international markets. IBAs can also understand their current position in terms of internationalisation support and think about new ways for improving this support. Originality/value - This paper contributes to a better understanding of the influence of institutional networks in SME internationalisation by exploring the specific role of one of the institutional actors rather than focusing on the institutional network as a whole. Therefore, this study details the current activities and uncovers other types of support provided by IBAs that are not based on export promotion programmes. New knowledge is also obtained about the specific information content, information sources and means and channels of information sharing used by IBAs for supporting SME internationalisation.

Abstract
This study addresses the product-launch planning problem in the chemical-pharmaceutical industry under technical and market uncertainties, and considering resource limitations associated to the need of processing in the same plant products under development and products in commercialization. A novel approach is developed by combining a mixed integer linear programming (MILP) model and a Monte Carlo simulation (MCS) procedure, to deal with the integrated process design and production planning decisions during the New Product Development (NPD) phase. The Monte Carlo simulation framework was designed as a two-step sampling procedure based on Bernoulli and Normal distributions. Results show the unquestionable influence of the uncertainty parameters on the decision variables and objective function, thus highlighting the inherent risks associated to the deterministic models. Process designs and scale-ups that maximize expected profit were determined, providing a valuable knowledge frame to support the long-term decision-making process, and enabling earlier and better decisions during NPD.

Abstract
Entry-only Automatic Fare Collection (AFC) systems are widely used in urban transports. Its main advantages include easy usability by passengers, improvement of the efficiency of revenue management, adequacy to integrate inter-modality approaches, easy cooperation between operators, systematic data collection and gathering tools, contributing to improve the planning process. This work starts with the literature review on applications of the Trip-Chaining Method (TCM) to the estimation of Origin-Destination (OD) matrices using entry-only AFC data. The main contribution of this study is to provide an OD matrix for the city of Porto, allowing to improve the quality of its public transport system. The paper reports the implementation of the TCM to estimate the alighting locations at the disaggregated level in the case study of Porto. The main assumptions adopted are: passengers start the next journey stage at or near the alighting location of their previous trip, passengers end the last trip of the day at the boarding location of the first trip of the day, passengers can only alight in the sequence of stops not yet traveled by the route / direction they boarded, passengers have a maximum interchange distance, above which the destination of that journey stage is not inferred. © 2017 The Authors. Published by Elsevier B.V.