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This paper analyses Rwandan farmers’ perceptions of historical drivers of landscape vulnerability (past), current livelihood assets (present) and existing or potential capacities (future) to increase resilience to drought. The specific focus is on linking experiences from the past and present with ideas for a drought-resilient future. It explores how farmers' perceptions of past droughts and future visioning can contribute to rural development policy and multi-level collaborations.

This study was conducted in Bugesera, a drought-prone district in south-eastern Rwanda. Empirical data was collected through participatory observation, semi-structured interviews and focus groups. The analytical points of departure are based on sustainable landscapes and livelihood approaches, combining spatial and temporal perspectives on challenges and opportunities identified by farmers’ communities in addressing droughts.

All respondents had a high awareness of the impact of droughts. Perceived drivers of landscape change include historical climate events, such as droughts and floods, immigration and agricultural expansion, which have led to demographic pressure on land, deforestation and infringement on natural resources. Factors enhancing resilience capacities include access to diversified sources of livelihood, knowledge of appropriate irrigation techniques and availability of safety nets and credits. Furthermore, farmers identified collaborative opportunities as important for resilience capacity, including peer learning, and sharing best practices through knowledge exchange and on-field training. In addition, farmers brought up the need for innovative institutions that can facilitate access to markets and enable collaboration between different agricultural sectors.

This study analyses farmers’ perceptions of resilience capacities to droughts through a spatiotemporal lens of past droughts, present capital and future challenges by linking scales, knowledge and human–environment nexus. This paper contributes to the knowledge of climate adaptation in Rwanda and to discussions about smallholder farming in the literature on climate change adaptation.

The purpose of this paper is to describe challenges the manufacturing industry is currently facing when developing future assembly information systems. More specific, this paper focuses on the handling of assembly information from manufacturing engineering to the shop floor operators.

Multiple case studies have been conducted within one case company between 2014 and 2017. To broaden the perspective, interviews with additionally 17 large and global manufacturing companies and 3 industry experts have been held. Semi-structured interviews have been the main data collection method alongside observations and web questionnaires.

Six focus areas have been defined which address important challenges in the manufacturing industry. For manual assembly intense manufacturing company, challenges such as IT challenges, process challenges, assembly process disturbances, information availability, technology and process control, and assembly work instructions have been identified and hinder implementation of Industry 4.0 (I4.0).

This longitudinal study provides a current state analysis of the challenges the manufacturing industry is facing when handling assembly information. Despite the vast amount of initiatives within I4.0 and digitalization, this paper argues that the manufacturing industry needs to address the six defined focus areas to become more flexible and prepared for the transition toward a digitalized manufacturing industry.

The purpose of this study intends to make a characterization of a shop floor management (SFM) system in the context of smart manufacturing, through smart technologies and digital shop floor (DSF) features.

To attain the paper objective, a mixed method methodology was used. In the first stage, a theoretical background was carried out, to provide a comprehensive understanding on SFM system in a smart manufacturing perspective. Next, a case study within a survey was developed. The case study was introduced to characterize a SFM system, while the survey was made to understand the level of influence of smart manufacturing technologies and of DSF features on SFM. In total, 17 experts responded to the survey.

Data analytics is the smart manufacturing technology that influences more the SFM system and its components and the cyber security technology does not influence it at all. The problem solving (PS) is the SFM component more influenced by the smart manufacturing technologies. Also, the use of real-time digital visualization tools is considered the most influential DSF feature for the SFM components and the data security protocols is the least influential one. The four SFM components more influenced by the DSF features are key performance indicator tracking, PS, work standardization and continuous improvement.

The study was applied in one multinational company from the automotive sector.

To the best of the authors’ knowledge, this work is one of the first to try to characterize the SFM system on smart manufacturing considering smart technologies and DSF features.