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Opportunistic and delayed maintenances are increasingly becoming important strategies for sustainable maintenance practices since they increase the lifetime of complex systems like aircrafts and heavy equipment. The objective of the current study is to quantify the optimal time window for adopting these strategies.

The current study considers the trade-offs between different costs involved in the opportunistic and delayed maintenances (of equipment) like the fixed cost of scheduled maintenances, the opportunistic rewards that may be earned and the cost of premature parts replacement. The probability of the opportunistic maintenance has been quantified under two different scenarios – Mission Reliability and Renewal Process. In the case of delayed maintenance, the cost of the delayed maintenance is also considered. The study uses optimization techniques to find the optimal maintenance time windows and also derive useful insights.

Apart from finding the optimal time window for the maintenance activities the study also shows that opportunistic maintenance is beneficial provided the opportunistic reward is significantly large; the cost of conducting scheduled maintenance in the pre-determined slot is significantly large. Similarly, the opportunistic maintenance may not be beneficial if the pre-mature equipment parts replacement cost is significantly high. The optimal opportunistic maintenance time is increasing function of Weibull failure rate parameter “beta” and decreasing function of Weibull failure rate parameter “theta.” In the case of optimal delayed maintenance time, these relationships reverse.

To the best of our knowledge, very few studies exist that have used mission reliability to study opportunistic maintenance or considered the different cost trade-offs comprehensively.

The purpose of this paper is to evaluate the reliability and signature reliability of solar panel k-out-of-n-multiplex system with the help of universal generating function.

Energy scarcity and global warming issues have become important concerns for humanity in recent decades. To solve these problems, various nations work for renewable energy sources (RESs), including sun, breeze, geothermal, wave, radioactive and biofuels. Solar energy is absorbed by solar panels, referred to as photovoltaic panels, which then transform it into electricity that can be used to power buildings or residences. Remote places can be supplied with electricity using these panels. Solar energy is often generated using a solar panel that is connected to an inverter for power supply. As a result, a converter reliability evaluation is frequently required. This paper presents a study on the reliability analysis of k-out-of-n systems with heterogeneous components. In this research, the universal generating function methodology is used to identify the reliability function and signature reliability of the solar array components. This method is commonly used to assess the tail signature and Barlow-Proschan index with independent and identically distributed components.

The Barlow-Proschan index, tail signature, signature, expected lifetime, expected cost and minimal signature of independent identically distributed are all computed.

This is the first study of solar panel k-out-of-n-multiplex systems to examine the signature reliability with the help of universal generating function techniques with various measures.

The artificial intelligence (AI) based total productive maintenance (TPM) condition based maintenance (CBM) approach through Industry 4.0 transformation can well predict the breakdown in advance to eliminate breakdown.

Meeting the customer requirement as per the delivery schedule with the existing resources are always a big challenge in industries. Any catastrophic breakdown in the equipment leads to increase in production loss, damage to machines, repair cost, time and affects delivery. If these breakdowns are predicted in advance, the breakdown can be addressed before its occurrence and the demand supply chain can be met. TPM is one of the essential operational excellence tool used in industries to utilize the existing resources of a plant in a optimal way. The conventional time based maintenance (TBM) and CBM approach of TPM in Industry 3.0 is time consuming and not accurate enough to achieve zero down time.

The proposed AI and IIoT based TPM is achieved in a digitalized data oriented platform to monitor and control the health status of the machine which may reduce the catastrophic breakdown by 95% and also improves the quality rate and machine performance rate. Based on the identified key signature parameters related to major breakdown are measured using the sensors, digitalised by programmable logic controller (PLC) and monitored by supervisory control and data acquisition (SCADA) and predicted in server or cloud.

Long short term memory based deep learning network was developed as a regression forecasting model to predict the remaining useful life RUL of the part or assembly and based on the predictions, corrective action has been implemented before the occurrence of breakdown. The reliability and consistency of the proposed approach are validated and horizontally deployed in similar machines to achieve zero downtime.

Optimizing manufacturing processes addresses operational challenges and yields significant benefits across the business spectrum. This study aims to comprehensively analyze a manufacturing process through value stream mapping (VSM), aiming to streamline operations, reduce production lead times and minimize work-in-process (WIP) inventory levels. These improvements directly enhance competitiveness, customer satisfaction and overall business success, enabling a swift response to market demands, timely delivery of high-quality products and cost-effectiveness.

The approach integrates current and future-state VSM concepts with Lean tools across four stages: problem definition, current-state VSM analysis, future-state VSM design and improvement implementation. A team assembled to improve the manufacturing process for electronic devices has successfully implemented this approach.

Implemented improvements significantly reduced WIP inventory (88.8% equivalent to $572,171 annually) and production lead time (from 28.26 to 3.21 days), enhancing operational flexibility and competitiveness. Streamlined processes led to a 13% decrease in cycle time and a notable reduction in daily rework (63.6%), amounting to $118,127 annually. Labor reduction (45.5%) yielded annual savings of approximately $594,000, with affected individuals successfully transitioning to other roles, highlighting the effectiveness of lean methodologies without job cuts.

This initiative exemplifies the effective use of VSM and Lean tools in optimizing an electronic device manufacturing operation that produces 43 products across various processes. By leveraging these methodologies, this research offers valuable insights into enhancing production efficiency, resulting in shorter production lead times, reduced cycle times and significant decreases in WIP inventory and rework.

The Purpose of this study is to prove the possibility of developing low cost mechanical anti – lock braking system (ABS) for the passenger’s safety.

The design methodology of the proposed newer mechanical ABS comprises of two units, namely, the braking unit and wheel lock prevention unit. The braking unit actuates the wheel stopping as and when the driver applies the brake, whereas the wheel lock prevention unit initiates wheel release to prevent locking and subsequent slip/skidding. The brake pedal with master cylinder assembly and double-arm cylinder forms the braking unit, brake pad cylinder, movable brake pad, solenoid valve and dynamo forms the wheel lock prevention unit. The dynamo coupled with the rotor energises/de-energises the solenoid values to direct airflow for applying brake and release it, which makes the system less energy-dependent.

The braking unit aids in vehicle stops, by locking the disc with the brake pad actuated by a double-arm cylinder. The dynamo energises the solenoid valve to activate the brake pad cylinder piston for applying the brake on the disc. Instantaneously, on applying the brake the dynamo de-energises the solenoid to divert the pneumatic flow for retracting the brake pad thereby minimizing the braking torque. The baking torque reduction revives the wheel rotating and prevents slip/skidding.

Mechanical ABS preventing wheel lock by torque reduction principle is a novel method that has not been evolved so far. The system was designed with repair/replacement of the parts and subcomponents to support higher affordability on safety grounds.

To address the high level of autistic unemployment it has been recommended that autistic individuals be supported to own and lead social enterprises. This paper aims to discuss what is required to create an enabling environment for autistic social entrepreneurship.

By referring to the autism, entrepreneurship and complexity theory literature, it is argued in this conceptual article that to create the required enabling environment for autistic social entrepreneurship, business advisors need to adopt a business development approach that aligns with autistic ways of thinking. It is also agrued that a place-based autistic social enterprise support ecosystem based on a landscape of practice approach is required to bring together diverse support individuals and organisations who have different approaches to practice. Examples including personal reflections are used to support these claims.

Challenges and barriers to creating the required enabling environment are identified. Two theories of change, one focused on creating integrated service delivery and one focused on enabling the landscape of practice to transition to a more effective state, are proposed for addressing the identified challenges and barriers.

To the best of the author’s knowledge, for the first time this article identifies what is required to address the challenges and barriers in creating an enabling environment for autistic social entrepreneurship. Without addressing these challenges and barriers there is a risk that nascent autistic social entrepreneurs will be set up for failure.

Despite opposition from housebuilders, the Nationally Described Space Standard (NDSS) was introduced in 2015 amid concerns about shrinking home sizes. This paper examines Planning Appeal cases to examine how the standard has been enforced.

This paper considers how the NDSS has informed the regulation of housing size, based on an overview of post-2015 Planning Appeal Decisions in England where the gross internal area of the home was below the NDSS.

Appeals by developers have tended to fail where homes are “significantly” – i.e. 10% or more – below the NDSS. However, in some instances – especially where local authorities have not adopted the NDSS – the Planning Inspectorate rules considerably smaller homes “adequate”. These discrepancies appear related to (subjective) judgements about who might occupy the space, alongside consideration of layout, light and fenestration.

This paper is the first exploration of how the NDSS has been enforced, highlighting important contradictions in the adjudication of space standards. Many of these contradictions emerge because the NDSS is discretionary rather than mandatory, with the paper suggesting the need for clearer guidance on their application.

This article aims to investigate how institutional characteristics affect the level of financial development of economies collectively and compare between developed and undeveloped economies.

A dynamic panel with 131 countries, including developed and developing ones, was utilized; the estimators of the generalized method of moments system (GMM system) model were selected because they have econometric characteristics more suitable for analysis, providing superior statistical precision compared to traditional linear estimation methods.

The results from the full panel suggest that concrete and well-defined institutions are important for financial development, confirming previous research, with a more limited scope than the present work.

Limitations of this research include the availability of data for all countries worldwide, which would make the research broader and more complete.

A panel of countries was used, divided into developed and developing countries, to analyze the impact of institutional variables on the financial development of these countries, which is one of the differentiators of this work. Another differentiator of this research is the presentation of estimates in six different configurations, with emphasis on the GMM system model in one and two steps, allowing for comparison between results.