This work analyses the influence of several design methods on the degree of creativity of the design outcome. A design experiment has been carried out in which the participants were divided into four teams of three members, and each team was asked to work applying different design methods. The selected methods were Brainstorming, Functional Analysis, and SCAMPER method. The ‘degree of creativity’ of each design outcome is assessed by means of a questionnaire offered to a number of experts and by means of three different metrics: the metric of Moss, the metric of Sarkar and Chakrabarti, and the evaluation of innovative potential. The three metrics share the property of measuring the creativity as a combination of the degree of novelty and the degree of usefulness. The results show that Brainstorming provides more creative outcomes than when no method is applied, while this is not proved for SCAMPER and Functional Analysis.

The size and complexity of industrial chemical plants, together with the nature of the products handled, means that an analysis and control of the risks involved is required. This paper presents a methodology for risk analysis in chemical and allied industries that is based on a combination of HAZard and OPerability analysis (HAZOP) and a quantitative analysis of the most relevant risks through the development of fault trees, fault tree analysis (FTA). Results from FTA allow prioritizing the preventive and corrective measures to minimize the probability of failure. An analysis of a case study is performed; it consists in the terminal for unloading chemical and petroleum products, and the fuel storage facilities of two companies, in the port of Valencia (Spain). HAZOP analysis shows that loading and unloading areas are the most sensitive areas of the plant and where the most significant danger is a fuel spill. FTA analysis indicates that the most likely event is a fuel spill in tank truck loading area. A sensitivity analysis from the FTA results show the importance of the human factor in all sequences of the possible accidents, so it should be mandatory to improve the training of the staff of the plants.

Job rotation is an organisational strategy widely used in human-based production lines with the aim of preventing work-related musculoskeletal disorders (WMSDs). These work environments are characterised by the presence of a high repetition of movements, which is a major risk factor associated with WMSDs. This article presents a genetic algorithm to obtain rotation schedules aimed at preventing WMSDs in such environments. To do this, it combines the effectiveness of genetic algorithms optimisation with the ability to evaluate the presence of risk by repeated movements by following the OCRA ergonomic assessment method. The proposed algorithm can design solutions in which workers will switch jobs with high repeatability of movements with other less demanding jobs that support their recovery. In addition, these solutions are able to diversify the tasks performed by workers during the day, consider their disabilities and comply with restrictions arising from the work organisation.

In the global construction context, the best value or most economically advantageous tender is becoming a widespread approach for contractor selection, as an alternative to other traditional awarding criteria such as the lowest price. In these multi-attribute tenders, the owner or auctioneer solicits proposals containing both a price bid and additional technical features. Once the proposals are received, each bidder’s price bid is given an economic score according to a scoring rule, generally called an economic scoring formula (ESF) and a technical score according to pre-specified criteria. Eventually, the contract is awarded to the bidder with the highest weighted overall score (economic + technical). However, economic scoring formula selection by auctioneers is invariably and paradoxically a highly intuitive process in practice, involving few theoretical or empirical considerations, despite having been considered traditionally and mistakenly as objective, due to its mathematical nature. This paper provides a taxonomic classification of a wide variety of ESFs and abnormally low bids criteria (ALBC) gathered in several countries with different tendering approaches. Practical implications concern the optimal design of price scoring rules in construction contract tenders, as well as future analyses of the effects of the ESF and ALBC on competitive bidding behaviour.