No abstract

PurposeIn this study, a frame of reference was developed to adapt and execute a continuous improvement process (CIP) for reinforcing a continuous improvement (CI) culture in an organisation. The study was undertaken in a mature capital goods company that did not succeed in institutionalising CI despite deploying many CI tools over the years. The organisation thus needed a model that was adapted to its reality and strengthened the aspects of CI through cultural changes at the organisational level.Design/methodology/approachAction research was used to implement the CIP, and this research method was reinforced using a hermeneutic phenomenological approach to analyse the results.FindingsThe CIP was validated in four units of analysis within the organisation. For the validation, aspects relevant to organisational cultural change and their metrics were identified. The results showed that the main barriers to the development of CI in the case organisation were lack of teamwork and poor assimilation of new CI routines.Research limitations/implicationsThe study was applied only in one organisation. Therefore, results cannot be generalized although the process and methodology followed to adapt and implement the CIP could be applied within other organisations.Originality/valueThe paper presents a CI frame of reference and describes how a CIP applied to a small- and medium-sized industrial enterprise generated cultural changes and promoted organisational excellence in the pursuit of CI, by using a hermeneutic phenomenological methodology approach.

No abstract

<p><strong>Purpose:</strong> The implementation of additive manufacturing (AM) or 3D-printer manufacturing for technical prototyping, preproduction series and short production series can bring benefits in terms of reducing cost and time to market in product development. These technologies are beginning to be applied in different industrial sectors and have a great possibility of development. As these technologies are still in development, there is a need to define the capacity of the 3D machines to establish minimum standards for producing high-quality parts.</p><p><strong>Methodology/Approach:</strong> The proposed methodology is based on a design of experiments (DOE) approach, which serves as a guide for engineers when it comes to executing any experimental study. The following steps were followed (Unzueta et al., 2019): Phase 1: define; Phase 2: measure; Phase 3: plan; Phase 4: execute experimentation; Phase 5: analyse the results; Phase 6: improve via confirmation experiments; Phases 7-8: control and standardise.</p><p><strong>Findings:</strong> The proposed methodology is based on a design of experiments (DOE) approach, which serves as a guide for engineers when it comes to executing any experimental study. The following steps were followed (Unzueta et al., 2019): Phase 1: define; Phase 2: measure; Phase 3: plan; Phase 4: execute experimentation; Phase 5: analyse the results; Phase 6: improve via confirmation experiments; Phases 7-8: control and standardise.</p><strong>Originality/Value of paper:</strong> This study uses a methodological approach to demonstrate how the 3D printing technology can be enriched with statistical testing techniques (DOE). It defines numerical prediction models to obtain high-quality parts with a new AM technology, using a planning process with a minimum amount of experimentation.

The motivation for research on 3D printing of protective face shields was the urgent societal demand for healthcare in the fight against the spread of COVID19 pandemic. Research is based on a literature review that shows that objects produced by additive technologies do not always have consistent quality suitable for the given purpose of use. Besides, they have different effects on the environment and leave different footprints. The overall goal of the research was to find out the most suitable thermoplastic material for printing shield frames in terms of mechanical properties, geometric accuracy, weight, printing time, filament price, and environmental sustainability. Fused deposition modeling (FDM) technology was used for 3D printing, and three different filaments were investigated: polylactic acid (PLA), polyethylene terephthalate (PETG), and polyhydroxyalkanoate (PHA). The weighted sum method for multi-objective optimization was used. Finally, PHA material was chosen, mainly due to its environmental sustainability, as it has the most negligible impact on the environment.