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The aim of this study is to develop an in-depth case study on the implementation on Lean six sigma (LSS) in Schnell S.p.A., Italian company leader of an important multinational industrial group, highlighting the benefits that can be achieved from a careful application of this method, the main challenges and organizational learning from its implementation.

The study has been developed with a qualitative approach, creating a single in-depth case study, with the participant observation of researchers in the project which lasted 4 months. Periodic weekly meetings were done with the working group to exchange feedback on the development of the project to share opinions and data.

A project has been developed to stabilize the procurement process of a pull-type production cell, which experienced delays in supply lead times. The causes of the problems in their process of managing the supply of the production cell were found and some inefficiencies in the internal process of fulfillment of supply orders have been intercepted, the optimization of which has allowed the generation of an automatic system for sending supply orders, coming directly from the production line.

This study described the path and dynamics of the transformation process that business organizations undertake for optimizing their profitability and competitive advantage, placing emphasis on an innovative methodology for conducting business process improvement projects, which constitutes its operating philosophy on the effective and efficient use of company resources and skills, to guarantee to the company the achievement of a lasting and defensible competitive advantage over time.

The purpose of this paper is to focus on three fundamental human-related behaviour factors associated with Lean Six Sigma (LSS) projects in German manufacturing small-and medium-sized enterprises (SMEs) on the readiness of people (managers and their staff) to commence LSS projects. These are core personal competence, strategic vision of the people and the organisational culture of the specific organisation.

Based on a thorough review of the academic literature a set of hypotheses were constructed to examine the level of association between people’s competence, vision and culture with LSS readiness within SMEs. This was done using correlation and regression analysis. Data collection were carried out in seven different German manufacturing SMEs involved in aerospace supply and agro-food manufacturing using a survey instrument.

It was found that there is a strong positive association between the core competence of people and organisational culture with readiness for commencing LSS in the manufacturing SMEs studied. The core values of people, education level and the vision of making continuous quality improvement were identified as key variables in promoting LSS readiness in these manufacturing SMEs. This study indicates that these “softer” variables can be essential to successful LSS implementation and need to be explored further before undertaking the process.

From the perspective of the implementers of LSS the results of this research could be of interest to different manufacturing SMEs intending to embark upon an LSS journey as it highlights the significance of human-related behavioural factors in the process. SME organisations may consider carrying out development or training with their managers and employees around personal and organisational values, addressing core competence and strengthening organisational culture in order to facilitate LSS readiness and enhance the prospect of its success.

It would appear that this LSS research has not been carried out within the German manufacturing SME context before and although discrete in nature has surfaced the “softer” variables of core competence of staff and organisational culture as important readiness issues to address when undertaking LSS. This integrated approach of human behavioural factors, organisational culture, LSS and manufacturing SMEs demonstrates the originality of the research.

There is compelling evidence that demonstrates that organisations are failing to reap the full benefits of lean initiatives. While much work has been conducted on what factors are critical to the success of lean initiatives, there is a dearth of empirical evidence relating to whether team leaders implement critical success factors (CSFs) in practice. Therefore, this study aims to explore the extent to which functional team leaders implement lean practices focussing on the role of leadership, empowerment and culture.

The research analysed team leaders in a single-site manufacturing organisation. A state-of-the-art analysis was conducted to isolate relevant themes and an instrument was developed to capture data. Empirical data was collected and analysed from 34 team leaders in engineering, quality and manufacturing.

The study found that while many good managerial practices to support lean is implemented, there remain significant challenges relating to cultural issues which must be addressed. The findings illuminate a latent gap in commitment and communication from senior management, as well as an underlying discrepancy in time and resource allocation.

The study’s findings provide new knowledge concerning the extent to which CSFs are implemented by functional team leaders in a real-world environment. The enquiry makes a valuable departure from previous research that focusses on leadership at a senior and middle manager level. It bridges the gap between academia and practice and provides tangible and concise results to management on how CSFs relating to leadership, empowerment and culture impact team leaders to drive lean methodologies.

This study aims to aid theory building, the use of decision theory (DT) concepts in sustainable supply chain management (SSCM) research is examined.

An abductive approach considers two DT concepts, Snowden’s Cynefin framework for sense-making and Keeney’s value-focussed decision analysis, in a systematic literature review of 160 peer-reviewed papers in English.

Around 60 per cent of the papers on decision-making in SSCM come from operational research (OR), which makes explicit use of DT. These are almost all normative and rationalist and focussed on structured decision contexts. Some exceptions seek to address unstructured decision contexts via Complex Adaptive Systems or Soft Systems Methodology. Meanwhile, a second set, around 16 per cent, comes from business ethics and are empirical, behavioural decision research. Although this set does not explicitly refer to DT, the empirical evidence here supports Keeney’s value-focussed analysis.

There is potential for theory building in SSCM using DT, but the research only addresses SSCM research (including corporate responsibility and ethics) and not DT in SCM or wider sustainable development research.

Use of particular decision analysis methods for SSCM may be improved by better understanding different decision contexts.

The research shows potential synthesis with ethical DT absent from DT and SCM research.

Empirical behavioural decision analysis for SSCM is considered alongside normative, rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM.

Empirical, behavioural decision analysis for SSCM is considered alongside normative rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM.

This paper aimed a fractional-order sliding mode-based lateral lane-change control method that was proposed to improve the path-tracking accuracy of vehicle lateral motion.

In this paper the vehicle presighting and kinematic models were established, and a new sliding mode control isokinetic convergence law was devised based on the fractional order calculus to make the front wheel turning angle approach the desired value quickly. On this basis, a fractional gradient descent algorithm was proposed to adjust the radial basis function (RBF) neuron parameter update rules to improve the compensation speed of the neural network.

The simulation results revealed that, compared to the traditional sliding mode control strategy, the designed controller eliminated the jitter of the sliding mode control, sped up the response of the controller, reduced the overshoot of the system parameters and facilitated accurate and fast tracking of the desired path when the vehicle changed lanes at low speeds.

This paper combines the idea of fractional order calculus with gradient descent algorithm, proposed a fractional-order gradient descent method applied to RBF neural network and fast adjustment the position and width of neurons.

The application of circular building adaptability (CBA) in adaptive reuse becomes an effective action for resource efficiency, long-lasting usability of the built environment and the sped-up transition to a circular economy (CE). This paper aims to explore to which extent CBA-related strategies are applied in adaptive reuse projects, considering enablers and obstacles.

A stepwise theory-practice-oriented approach was followed. Multiple-case studies of five circular adaptive reuse projects in The Netherlands were investigated, using archival research and in-depth interviews. A cross-case analysis of the findings was deductively conducted, to find and replicate common patterns.

The study revealed that configuration flexibility, product dismantlability and material reversibility were applied across the case studies, whereas functional convertibility and building maintainability were less applied. Low cost of material reuse, collaboration among team members and organisational motivation were frequently observed enabling factors. Lack of information, technical complexities, lack of circularity expertise and infeasibility of innovative circular solutions were frequently observed obstacles to applying CBA.

This paper provides practitioners with a set of CBA strategies that have been applied in the real world, facilitating the application of CBA in future adaptive reuse projects. Moreover, this set of strategies provides policymakers with tools for developing supportive regulations or amending existing regulations for facilitating CE through adaptive reuse.

This study provides empirical evidence on the application of CBA in different real-life contexts. It provides scholars and practitioners with a starting point for further developing guiding or decision-making tools for CBA in adaptive reuse.

This paper aims to discuss the development of a defect classification system that can be used to detect and classify powder bed surface defects from captured layer images without the need for specialised computational hardware. The idea is to develop this system by making use of more traditional machine learning (ML) models instead of using computationally intensive deep learning (DL) models.

The approach that is used by this study is to use traditional image processing and classification techniques that can be applied to captured layer images to detect and classify defects without the need for DL algorithms.

The study proved that a defect classification algorithm could be developed by making use of traditional ML models with a high degree of accuracy and the images could be processed at higher speeds than typically reported in literature when making use of DL models.

This paper addresses a need that has been identified for a high-speed defect classification algorithm that can detect and classify defects without the need for specialised hardware that is typically used when making use of DL technologies. This is because when developing closed-loop feedback systems for these additive manufacturing machines, it is important to detect and classify defects without inducing additional delays to the control system.

Analysis of characteristic driving operations can help develop supports for drivers with different driving skills. However, the existing knowledge on analysis of driving skills only focuses on single driving operation and cannot reflect the differences on proficiency of coordination of driving operations. Thus, the purpose of this paper is to analyze driving skills from driving coordinating operations. There are two main contributions: the first involves a method for feature extraction based on AdaBoost, which selects features critical for coordinating operations of experienced drivers and inexperienced drivers, and the second involves a generating method for candidate features, called the combined features method, through which two or more different driving operations at the same location are combined into a candidate combined feature. A series of experiments based on driving simulator and specific course with several different curves were carried out, and the result indicated the feasibility of analyzing driving behavior through AdaBoost and the combined features method.

AdaBoost was used to extract features and the combined features method was used to combine two or more different driving operations at the same location.

A series of experiments based on driving simulator and specific course with several different curves were carried out, and the result indicated the feasibility of analyzing driving behavior through AdaBoost and the combined features method.

There are two main contributions: the first involves a method for feature extraction based on AdaBoost, which selects features critical for coordinating operations of experienced drivers and inexperienced drivers, and the second involves a generating method for candidate features, called the combined features method, through which two or more different driving operations at the same location are combined into a candidate combined feature.

Interprofessional practice (IPP) is one way to structure collaborations to more effectively meet the complex needs of students in educational settings. This article explores the lessons learned when one research team implemented interprofessional education (IPE) experiences in partnership with a public elementary school and pre-service professionals from elementary education, special education and communication science and disorders.

This reflective article explores the lived experiences of researchers and partners who completed an IPE experience within one professional development school’s site. Researcher anecdotes are included to support the viewpoints shared.

It was discovered that IPE experiences are essential to facilitate meaningful collaborations for pre-service professionals to learn with and from one another; however, this requires time, preparation and is most effective when teacher mentors and university professors lead with vulnerability and model flexibility. Investment in IPE is challenging but worth the effort when learning outcomes are realized.

Specific details regarding the structure of this experience are shared as well as future directional goals for programs hoping to implement IPE in their professional practice programs.

This study aims to analyze the development direction of train speed, density and weight in China.

The development of China's railway in the past 40 years can be divided into 3 stages. At the stage of potential tapping and capacity expansion, it is important to improve the train weight and density by upgrading the existing lines, and improving transportation capacity rapidly. At the stage of railway speed increase, the first priority is to increase train speed, reduce the travel time of passenger train, and synchronously take into account the increase of train density and weight. At the stage of developing high-speed railway, train speed, density and weight are co-developing on demand.

The train speed of high-speed railway will be 400 km h⁻¹, the interval time of train tracking will be 3 min, and the traffic density will be more than 190 pairs per day. The running speed of high-speed freight EMU will reach 200 km h⁻¹ and above. The maximum speed of passenger train on mixed passenger and freight railway can reach 200 km h⁻¹. The minimum interval time of train tracking can be compressed to 5 min. The freight train weight of 850 m series arrival-departure track railway can be increased to 4,500–5,000 t and that of 1,050 m series to 5,500–6,400 t. EMU trains should gradually replace ordinary passenger trains to improve the quality of railway passenger service. Small formation trains will operate more in intercity railway, suburban railway and short-distance passenger transportation.

The research can provide new connotations and requirements of railway train speed, density and weight in the new railway stage.