Purpose: Identifying possible ergonomic risks generated by the implementation of Lean Manufacturing in organizations. Shows a need to integrate ergonomics and productivity indicators in process analysis, thus giving place to the ErgoVSM methodology, which is VSM (Value Stream Mapping) complemented with ergonomic analysis.Design/methodology/approach: This literature review aims to refer to the methodology and instruments used for its application, as well as the benefits obtained and the challenges that arise when applying it.Findings: This article presents a review of 26 publications regarding the ErgoVSM methodology. The ErgoVSM is mainly based on the VSM methodology developed by Rother & Shook that is most applied in the healthcare sector with ergonomic analysis instruments that focus on the physical and psychosocial factors of the workers.Originality/value: The review revealed that when using ErgoVSM, processes can be improved from the ergonomic perspective without negatively affecting productivity. Even though ErgoVSM requires more time for application compared to VSM, the value of the ergonomic data for decision making in process changes justifies the extra time.

The human factor is becoming increasingly relevant for its role in industrial development; therefore, it is necessary to evaluate the machine–man–environment system in an integrated and not isolated way, as is commonly done, for evaluating the sustainability performance of manufacturing practices. For this reason, in this paper, an ergonomic triad model is proposed for calculating a novel Sustainable Work Index, (SWI), made up of the factors: human work, workstation design, organizational environment and sustainable environmental conditions. The methodology consists of defining the productive time, interviewing the workers, taking anthropometric measurements, assessing the environmental conditions, obtaining the indicators for each factor, calculating the index and interpreting the results to define improvement actions. The model was applied to a manufacturing industry obtaining a regular status with an index of 63.6%. Improvement actions were implemented, and it was possible to increase the index to 73.9%, which represents a good commitment of the company towards occupational health. The development of the new triad model to calculate the SWI will allow industries to visualize indicators of the interaction of the ergonomic triad, identify its current condition and propose actions to physically, organizationally and environmentally improve human well-being and system performance.

The Integral Ergonomic-Value Stream Mapping (Ergo-VSM) methodology is introduced in this study, which is tailored for the metal-mechanic sector and aims to assess the operational and ergonomic conditions of production processes. The methodology is designed to identify ergonomic risks and propose an improvement plan to increase productivity by integrating ergonomic measurement instruments aligned with official standards and lean manufacturing tools such as VSM and Kaizen. The study, which was conducted in a metal-mechanical MSME (micro, small and medium enterprises), resulted in an 11.8% overall improvement in psychosocial risk factors, a 4.4% increase in productivity with a 1.96-h reduction in cycle time, and a 20% decrease in reported quality rejections. Notably, the study shows that the Integral Ergo-VSM can be implemented in a variety of organizational contexts, ensuring adaptability without jeopardizing the methodology’s core objectives.

Purpose: The purpose of this work is to present a method based on the application of method engineering, in order to eliminate downtime and improve the manufacturing cell.Design/methodology/approach: The research strategy employed was a case study applied to a manufacturing company to explore the causes of excessive dead time and low productivity. The methodology used was divided in five steps. The first corresponds to the analysis of the lathe and grinding process; the second is the elaboration of the man-machine diagram to identify dead times; the third is the application of the improvement proposal; the fourth is the redistribution of the cell to optimize the process; the fifth is to conclude from the results obtained.Findings: With the proposed method, the downtime was reduced by 41% and only 50% of the available labor is required, therefore, it is concluded that the method can be used to redesign manufacturing cells.Research limitations/implications: This research was limited to analyzing and improving human-machine interaction, since work is not just the machine, or the individual alone, or the individual manipulating the machine, therefore, no other tools were used to improve the time of machines operation.Practical implications: Designing a manufacturing cell that allows the operator to do his job with less fatigue and not adapt the operator to the job, as commonly happens.Social implications: Companies must show a greater interest in occupational health by including human capital in their optimization plans to avoid future harm to workers.Originality/value: The key contribution of this paper focused on developing a novel and practical methodology to design or re-design manufacturing cells to improve productivity considering the human factor, inspired by the main concepts of method engineering.

As interest in additive manufacturing (AM) continues to increase, it has become more important to have a robust method to help potential users select the AM process that best suits their technological needs while providing the greatest potential benefits in terms of sustainability and its effect on people. This paper presents the development of a framework for selecting the best AM process for a given application by considering both sustainability and human factors through the combination of axiomatic design and the analytic hierarchy process. Thirty-one participants with varying levels of expertise (novice and advanced users) were involved in the study, considering the frequency of 3D printer usage (novice users: never, rarely; expert users: sometimes, almost always, always) for prototyping parts. They employed fused deposition modeling (FDM) and stereolithography (SLA) (both 3D desktop printers) and collected data on five evaluation criteria. The participation of experts helped establish a novel methodology, with material cost deemed most important (49.8%), followed by cycle time (28%), energy consumption (11.7%), error rate (6.6%), and equipment noise (3.9%). The results showed that FDM was the optimal equipment option for advanced users. By examining the information content of the other options, it was found that FDM demanded less information than SLA, regardless of the user’s level of expertise. The proposed method is appropriate to assess the sustainability aspect of FDM and SLA; however, it can be further improved by adding indicators such as environmental impact, recyclability, and ergonomic and occupational health factors.