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Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.

Combining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.

Application of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.

The results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.

To the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.

The United Nations' Sustainable Development Goal of ensuring healthy lives and promoting well-being for people of all ages underscores the vital role of public healthcare facilities (PHFs) in delivering essential healthcare services. However, these facilities often suffer from inadequate maintenance, exacerbated by the insufficient implementation of maintenance strategies. Recognizing the importance of PHFs in enhancing healthcare services, this paper investigates the Critical Success Factors (CSFs) in the maintenance strategies of PHFs in South Africa.

Through semi-structured interviews with nineteen purposively selected maintenance personnel from the Limpopo Department of Health (DoH), this study identified and analyzed the CSFs to enhance maintenance operations in PHFs. Thematic content analysis was employed to derive key insights from the collected data.

The study's findings highlight adequate maintenance planning and effective leadership as the two overarching CSFs in the maintenance of PHFs. These factors play a pivotal role in addressing challenges that hinder the current maintenance team from meeting maintenance requirements to the satisfaction of both staff and patients within PHFs.

The study offers valuable insights for policymakers to improve the effectiveness of maintenance operations in PHFs. By addressing the identified CSFs, policymakers can enhance maintenance operations in PHFs, positively impacting healthcare service delivery and the well-being of both staff and patients.

Steam explosions are a major safety concern in many modern furnaces. The explosions are sometimes caused by water ingress into the furnace from leaks in its high-pressure (HP) cooling water system, coming into contact with molten matte. To address such safety issues related to steam explosions, risk based inspection (RBI) is suggested in this paper. RBI is presently one of the best-practice methodologies to provide an inspection schedule and ensure the mechanical integrity of pressure vessels. The application of RBIs on furnace HP cooling systems in this work is performed by incorporating the proportional hazards model (PHM) with the RBI approach; the PHM uses real-time condition data to allow dynamic decision-making on inspection and maintenance planning.

To accomplish this, a case study is presented that applies an HP cooling system data with moisture and cumulated feed rate as covariates or condition indicators to compute the probability of failure and the consequence of failure (CoF), which is modelled based on the boiling liquid-expanding vapour explosion (BLEVE) theory.

The benefit of this approach is that the risk assessment introduces real-time condition data in addition to time-based failure information to allow improved dynamic decision-making for inspection and maintenance planning of the HP cooling system. The work presented here comprises the application of the newly proposed methodology in the context of pressure vessels, considering the important challenge of possible explosion accidents due to BLEVE as the CoF calculations.

This paper however aims to optimise the inspection schedule on the HP cooling system, by incorporating PHM into the RBI methodology, as was recently proposed in the literature by Lelo et al. (2022). Moisture and cumulated feed rate are used as covariate. At the end, risk mitigation policy is suggested.

In this paper, the proposed methodology yields a dynamically calculated quantified risk, which emphasised the imperative for mitigating the risk, as well as presents a number of mitigation options, to quantifiably affect such mitigation.

Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues, causing service disruptions and cost overruns. These defects can be avoided if a link between the early design stages and maintenance feedback is established. This study aims to use experts’ experience in HVAC maintenance in health-care facilities to list and evaluate the risk of each maintenance issue caused by a design defect, supported by the literature.

Following semistructured interviews with experts, 41 maintenance issues were identified as the most encountered issues. Subsequently, a survey was conducted in which 44 participants evaluated the probability and impact of each design-caused issue.

Chillers were identified as the HVAC components most prone to design defects and cost impact. However, air distribution ducts and air handling units are the most critical HVAC components for maintaining healthy conditions inside health-care facilities.

The unavailability of comprehensive data on the cost impacts of all design-related defects from multiple health-care facilities limits the ability of HVAC designers to furnish case studies and quantitative approaches.

This study helps HVAC designers acquire prior knowledge of decisions that may have led to unnecessary and avoidable maintenance. These design-related maintenance issues may cause unfavorable health and cost consequences.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

This paper integrates the action phase theory (APT) and the theory of planned behaviour (TPB) to analyse the dynamic mechanisms involved in the configuration of goals and implementation intentions throughout the entrepreneurship process.

The empirical analysis compares individuals in different phases of this process (not yet decided, potential and nascent entrepreneurs). A large sample of adults from Spain is analysed. Structural equation models and multi-group analysis (MGA) serve to test the hypotheses.

The results confirm that perceived behavioural control (PBC) is the most influential antecedent of entrepreneurial goal intention (EGI) in pre-actional phases (undecided and potential entrepreneurs), whilst attitude towards entrepreneurship (ATE) takes this role during nascency. Subjective norms (SNs) are more important in Phase 1 (establishing the goal) and in Phase 3 (performing nascent behaviour).

This study contributes to both the TPB and the APT. It provides the most relevant insight into the mental process that leads to starting up and helps explain certain previous conflicting results found in the literature. Additionally, it has important implications not only for theory building but also for support bodies and for entrepreneurship educators.

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment effectiveness (OEE) tool to enhance the process performance and establish Fourth Industrial Revolution (I4.0) platform in small and medium enterprises (SMEs).

This work utilised plan, do, check, act Lean methodology to create a digital twin of each machine in a smart manufacturing facility by taking the Lean tool OEE and digitally transforming it in the context of I4.0. To demonstrate the effectiveness of process digitisation, a case study was carried out at a manufacturing department to provide the data to the model and later validate synergy between Lean and I4.0 platform.

The OEE parameter can be increased by 10% using a proposed digital twin model with the introduction of a Level 0 into VM platform to clearly define the purpose of each data point gathered further replicate in projects across the value stream.

The findings suggest that researchers should look beyond conversion of stored data into visualisations and predictive analytics to improve the model connectivity. The development of strong big data analytics capabilities in SMEs can be achieved by shortening the time between data gathering and impact on the model performance.

The novelty of this study is the application of OEE Lean tool in the smart manufacturing sector to allow SME organisations to introduce digitalisation on the back of structured and streamlined principles with well-defined end goals to reach the optimal OEE.

This study describes how a multinational enterprise (MNE) gains acceptance after rebranding acquired brands from different countries among its internal and external stakeholders and identifies factors that influence this process.

The study employed a single case-study approach, including 18 semi-structured in-depth interviews with employees of a firm involved in the rebranding process in six countries. The countries are Sweden, Germany, the United States, Brazil, Colombia and Mexico.

The findings reveal how the MNE integrated brands it acquired in different international markets into one overarching corporate brand. The study shows that in emerging countries, external legitimation (external implementation process, country profiles and customer buy-in) constitutes the most significant challenge. By contrast, in developed countries, internal legitimation (employee buy-in and internal implementation process) is more challenging.

The study contributes to and extends the rebranding literature by using a legitimation lens to analyze the rebranding process. This lens shows how internal and external stakeholders are both crucial to successful rebranding. The study provides a comprehensive perspective of the process, identifies challenging factors and differentiates between their importance in emerging and developed countries.

To address the dearth of research on how firms legitimize a new brand in different national contexts, the study compares the rebranding process in multiple countries and discusses the factors influencing the rebranding process.

This study aims to present the concept of aircraft turbofan engine health status prediction with artificial neural network (ANN) pattern recognition but augmented with automated features engineering (AFE).

The main concept of engine health status prediction was based on three case studies and a validation process. The first two were performed on the engine health status parameters, namely, performance margin and specific fuel consumption margin. The third one was generated and created for the engine performance and safety data, specifically created for the final test. The final validation of the neural network pattern recognition was the validation of the proposed neural network architecture in comparison to the machine learning classification algorithms. All studies were conducted for ANN, which was a two-layer feedforward network architecture with pattern recognition. All case studies and tests were performed for both simple pattern recognition network and network augmented with automated feature engineering (AFE).

The greatest achievement of this elaboration is the presentation of how on the basis of the real-life engine operational data, the entire process of engine status prediction might be conducted with the application of the neural network pattern recognition process augmented with AFE.

This research could be implemented into the engine maintenance strategy and planning. Engine health status prediction based on ANN augmented with AFE is an extremely strong tool in aircraft accident and incident prevention.

Although turbofan engine health status prediction with ANN is not a novel approach, what is absolutely worth emphasizing is the fact that contrary to other publications this research was based on genuine, real engine performance operational data as well as AFE methodology, which makes the entire research very reliable. This is also the reason the prediction results reflect the effect of the real engine wear and deterioration process.

The Recast Energy Efficiency Directive 2023 has defined the concept of “split incentive,” also known as “tenant-owner dilemma.” This dilemma refers to the situation where neither landlords nor tenants have incentives to invest in energy efficiency upgrades. Although the Energy Efficiency Directive calls Member States to overcome legal barriers to remove split incentives and to encourage retrofits, the list of possible measures is too vague. This paper aims to discuss tenancy law measures designed to increase the energy efficiency of residential housing and to detect which Member States have already addressed this phenomenon.

This paper analyses, from a civil legal perspective, the possible private law barriers arising from the tenant-owner dilemma when performing energy efficiency works in selected countries and proposes legal reforms in tenancy law and related policies to overcome them. To do so, this paper follows a legal-dogmatic and comparative law methodology.

This paper concludes that some tenancy law provisions, such as the possibility to increase the rent after energy efficiency renovations and long-term leases, may challenge the tenant-owner dilemma in private rented markets, thus promoting renovations and retrofitting for energy efficiency purposes. It also proposes other policies intended to increase parties’ willingness to undertake works.

More research on the economic and legal efficiency to regulate some of the civil law measures to challenge the tenant-owner dilemma should be necessary.

The civil law measures included in this paper may help national policymakers meet the energy efficiency targets, according to what is established in the Recast Energy Efficiency Directive 2023.

Based on the economic theory of the tenant-owner dilemma, this paper investigates the elements of tenancy law that may contribute to less energy-efficient homes, proposing policies for those countries interested in addressing the energy-efficiency challenge from a private law point of view.