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This paper presents a new metric for describing the sustainability improvements achieved, relative to the company's initial situation, after implementing a lean and green manufacturing system. The final value of this metric is identified as the Overall Environmental Equipment Effectiveness (OEEE), which is used to analyze the evolution between two identified states of the Overall Equipment Effectiveness (OEE) and the sustainability together, and references, globally and individually, the production steps. The OEE is a known measure of equipment utilization, which includes the availability, quality and performance of each production step, In addition to these factors, the OEEE incorporates the concept of sustainability based on the calculated environmental impact of the complete product life cycle. Action research based on the different manufacturing processes of a tube fabrication company is conducted to assess the potential impact of this new indicator. The case study demonstrates the compatibility between green and lean manufacturing, using a common metric. The OEEE allows sustainability to be integrated into business decisions, and compares the environmental impact of two states, by identifying the improvements undertaken within the company's processes.

BackgroundMusculoskeletal disorders (MSDs) that result from poor ergonomic design are one of the occupational disorders of greatest concern in the industrial sector. A key advantage in the primary design phase is to focus on a method of assessment that detects and evaluates the potential risks experienced by the operative when faced with these types of physical injuries. The method of assessment will improve the process design identifying potential ergonomic improvements from various design alternatives or activities undertaken as part of the cycle of continuous improvement throughout the differing phases of the product life cycle.Methodology/Principal FindingsThis paper presents a novel postural assessment method (NERPA) fit for product-process design, which was developed with the help of a digital human model together with a 3D CAD tool, which is widely used in the aeronautic and automotive industries. The power of 3D visualization and the possibility of studying the actual assembly sequence in a virtual environment can allow the functional performance of the parts to be addressed. Such tools can also provide us with an ergonomic workstation design, together with a competitive advantage in the assembly process.ConclusionsThe method developed was used in the design of six production lines, studying 240 manual assembly operations and improving 21 of them. This study demonstrated the proposed method’s usefulness and found statistically significant differences in the evaluations of the proposed method and the widely used Rapid Upper Limb Assessment (RULA) method.

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PurposeThis paper seeks to analyse the internal materials flow in lean manufacturing in an assembly line of the Bosch factory, located in Spain. The objective is to develop a handling system in a small space, capable of solving the problems of accumulated intermediate stocks of parts. An improvement is proposed adopting the milkrun handling system, while verifying the advances by means of lean metrics.Design/methodology/approachBased on this case study, the paper identifies data from value stream mapping and uses lean metrics, such as dock‐to‐dock time and lean rate. The case study develops a timetable and routing analysis for the milkrun to improve materials flow.FindingsThe proposed logistics allows an improvement of lean metrics, without modifying the layout and production planning. The routing flexibility of the milkrun reduced stocks, work‐in‐process and dock‐to‐dock time, while increasing lean rate.Research limitations/implicationsThe findings are limited due to the focused nature of the case study. Although the solution is designed for a particular plant, the methodology is fully exportable.Practical implicationsThe paper shows a real case study illustrative for systems management. This research shows significant benefit associated with the implementation of lean programs.Originality/valueIt details how the application of lean manufacturing tools could necessitate a study of materials handling to improve lean metrics.

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Electromyography (EMG) signals are biomedical signals that measure electrical currents generated during muscle contraction. These signals are strongly influenced by physiological and anatomical characteristics of the muscles and represent the neuromuscular activities of the human body. The evolution of EMG analysis and acquisition techniques makes this technology more reliable for production engineering applications, overcoming some of its inherent issues. Taking as an example, the fatigue monitoring of workers as well as enriched human–machine interaction (HMI) systems used in collaborative tasks are now possible with this technology. The main objective of this research is to evaluate the current implementation of EMG technology within production engineering, its weaknesses, opportunities, and synergies with other technologies, with the aim of developing more natural and efficient HMI systems that could improve the safety and productivity within production environments.