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This paper presents tools and equipment aspects of the results from a three‐year United Kingdom Government funded research project investigating accident causality (ConCA). The project has used focus groups and studied in detail 100 construction accidents site audits, interviews with involved persons and follow‐up along the causal chain. This paper concentrates on the influence of construction tools and equipment which were found to be important contributory factors identified by the research. They have largely been overlooked by previous studies and are not typically acknowledged as accident contributors. This paper argues for further work to confirm these links and for the inclusion of tools and equipment in the list of categories in statutory reporting procedures. This would also require an increased acknowledgement by construction managers of their influence, leading to better design and management of their supply and care on site.

The development of an insole that is representative of the foot's dynamic nature is crucial for good fit as well as comfort and performance. Additive manufacturing (AM) has the potential to allow the production of such insoles because of its tool-less capabilities and the ability to directly manufacture from CAD models at no extra cost. Research therefore has been undertaken to explore a process of foot capture by using a dynamic scanner for the design and manufacture of insoles using AM. The feet of four individuals were dynamically and statically scanned and from these data, four insole designs were developed for each person. The designs were: footprint, dynamic, average and static. The results indicated that the personalisation process is complex, mainly due to the need to identify and select the point cloud(s) from a large number of frames and manipulate them accordingly, presenting challenges in the design phase. The data from this study have demonstrated that combining dynamic scanning and AM technology is feasible for developing personalised insoles. While traditional footwear/insole is based on static data, this study can be considered as a starting point for the development of personalised insoles by using dynamic scanning and AM.