Many industries rely heavily on the availability and reliability of complex structural and functional components to execute operations efficiently. However, failure of components during service occurs due to exposure to unfavourable operating conditions, causing wear and tear of these components. The damage will result in costly downtime and potential safety hazards. Repairing, remanufacturing and refurbishing these complex parts is critical. Restoring broken structures into operation ensures the smooth operation of the industry, thus preventing losses. Conventionally, repairing parts poses a challenge. However, Wire-arc additive manufacturing (WAAM), which employs the welding principle, has revolutionised component repairing or remanufacturing. This paper reviews the literature on manufacturing complex parts, repair, remanufacture and refurbishment of broken structural and functional parts using WAAM technology. This paper also highlights the various strategies and techniques currently used to improve the quality of WAAM 3D printed parts. The study further covers the immense potential of WAAM in revolutionising the remanufacturing and repair of components. The review study has provided a roadmap for future research and development to take full advantage of this new cutting-edge manufacturing technology.

Modern Smart Cities are highly dependent on an efficient energy service since electricity is used in an increasing number of urban activities. In this regard, Time-of-Use prices for electricity is a widely implemented policy that has been successful to balance electricity consumption along the day and, thus, diminish the stress and risk of shortcuts of electric grids in peak hours. Indeed, residential customers may now schedule the use of deferrable electrical appliances in their smart homes in off-peak hours to reduce the electricity bill. In this context, this work aims to develop an automatic planning tool that accounts for minimizing the electricity costs and enhancing user satisfaction, allowing them to make more efficient usage of the energy consumed. The household energy consumption planning problem is addressed with a multiobjective evolutionary algorithm, for which problem-specific operators are devised, and a set of state-of-the-art greedy algorithms aim to optimize different criteria. The proposed resolution algorithms are tested over a set of realistic instances built using real-world energy consumption data, Time-of-Use prices from an electricity company, and user preferences estimated from historical information and sensor data. The results show that the evolutionary algorithm is able to improve upon the greedy algorithms both in terms of the electricity costs and user satisfaction and largely outperforms to a large extent the current strategy without planning implemented by users.

The paradigm of the cyber-physical manufacturing system is playing an increasingly important role in the development of production systems and management of manufacturing processes. This paper presents an optimization model for solving an integrated problem of production planning and manufacturing control. The goal is to create detailed production plans for a complex manufacturing system and to control the skilled manual workers. The detailed optimization model of the problem and the developed approach and algorithms are described in detail. To consider the impact of human workers performing the manufacturing primary operations, we elaborated an extended simulation-based procedure and new multi-criteria control algorithms that can manage varying availability constraints of parallel workstations, worker-dependent processing times, different product types and process plans. The effectiveness of the proposed algorithms is demonstrated by numerical results based on a case study.

The effect of air injection into a coffee roasting chamber of a 2 kg rotary drum roaster is investigated on the temperature profiles and organoleptic properties of a Catuai coffee variety. In the experimental study, 1 kg of coffee beans were used and the air injection velocities were varied for the cases of 0 (standard roasting design), 1, 2 and 3 m/s; testing in triplicate and the two most representative were taken. In the coffee roaster, the temperature was monitored simultaneously in the air inlet duct, roasting chamber and gas outlet duct. The organoleptic properties were examined by a group of professionals from Negociaciones Agroindustrial Arévalo S.A. NARSA in the province of Chanchamayo - Peru, which has a G4 laboratory certified by the Specialty Coffee Association (SCA). In the organoleptic ratings, a maximum score of 83.21/100 was found for the 2 m/s test and a minimum of 80.63/100 for the 1 m/s test. For the numerical characterization, the principle of fluid mechanics such as turbulent regime flow and energy transport were used by the finite volume (FV) method using SolidWorks 2021 Flow Simulation software. The numerical results showed that for the 2 m/s test, the temperature of the bean reaches 195 oC at 500 s, indicating that the whole coffee bean reaches the cooking temperature required for the development time prior to eviction; while for the 1 m/s test, it did not exceed 190 oC. It is shown here that the effect of air injection in the roasting chamber, caused organoleptic changes with respect to the conventional design without air injection, due to a sustained cooking at different times and an adequate development time. However, there is a speed threshold where when exceeded, temperatures inside the chamber remain low, development time is extended (machine energy consumption is extended), and organoleptic properties should not improve. However, as the test speeds are exceeded, temperatures inside the chamber remain low, causing the development time to be extended with higher energy consumption and under these conditions the organoleptic properties are not improved.

Adhesive joints play a vital role in different industries owing to their advantages and ease of application compared to other joining methods. This research focuses on enhancing the mechanical properties of epoxy adhesives by incorporating graphene nanoplatelets (G) and iron-oxide nanofillers (Fe3O4). Single-lap adhesive joints, including both G and Fe3O4 nanoparticles, are fabricated at 2%, 3%, and 4% weight percentages and tested under tensile load at ambient, 45°C, and 88°C. The results reveal that adding G and Fe3O4 nanofillers enhances shear strength at elevated and room temperatures without altering the epoxy glass transition temperature (Tg). Furthermore, G nanofiller performs better in improving shear strength than Fe3O4. The optimal weight percentage is identified as 3 wt% for G and Fe3O4, as higher percentages lead to decreased shear strength due to agglomeration

The combined effect of serial dependency and measurement errors is known to negatively affect the statistical efficiency of any monitoring scheme. However, for the recently proposed homogenously weighted moving average (HWMA) scheme, the research that exists concerns independent and identically distributed observations and measurement errors only. Thus, in this paper, the HWMA scheme for monitoring the process mean under the effect of within-sample serial dependence with measurement errors is proposed for both constant and linearly increasing measurement system variance. Monte Carlo simulation is used to evaluate the run-length distribution of the proposed HWMA scheme. A mixed-s&m sampling strategy is incorporated to the HWMA scheme to reduce the negative effect of serial dependence and measurement errors and its performance is compared to the existing Shewhart scheme. An example is given to illustrate how to implement the proposed HWMA scheme for use in real-life applications.

Fatigue crack growth studies require models that accurately predict component life with low uncertainty. Despite the large number of proposed models, there is no clarity on their applicability, which justifies a comparative analysis between some of them. The dual boundary element method (DBEM) was applied for cracked bodies, whereby the stress intensity factors (SIF), the growth rate, and the number of cycles were computed. Three crack increment models were studied under constant amplitude fatigue loads: the Paris, the Klesnil-Lucas, and the Forman models. Results were validated with experimental literature and through the finite element method, indicating that each model represents a specific zone of the crack growth curve. Klesnil-Lucas model reproduces the region near the fracture threshold, Paris fits the controlled crack growth zone, whereas Forman’s model recreates the unstable fracture zone, i.e., when the stress intensity factor approaches the material’s fracture toughness. The J-integral with stress field decomposition gave errors below 0.8% for mode I. Results were similar for the propagation path and the number of cycles to those obtained with the finite element method, with errors of about 3% considering different K-effective approaches. Klesnil-Lucas accurately predicts the number of cycles with an error margin below 3%, considering the curved region in the growth rate at the propagation onset, while the Paris model becomes very conservative, predicting values up to 50% lower than experimental data. The Klesnil-Lukas model is advised for simulating the entire crack propagation.

Efficient business organizations must balance quality, cost, and time constraints in competitive environments. Reflecting the complexity of this task, we consider manufacturing systems including several stages of production chains requiring time measurement. When production scheduling is not prioritized in such enterprises, several negative effects may occur. A corporation may suffer financial penalties as well as negative brand exposure, and thus may find its credibility challenged. Therefore, in this study, we propose constructive methods to minimize a total tardiness criterion, considering preventative maintenance constraints to reflect the reality of industrial practice, focusing on a no-wait flowshop environment in which jobs are successively processed without operational interruptions. In addition to proposing constructive methods to solve the no-wait flowshop production scheduling problem, a metaheuristic is presented as an approach to improve results obtained by constructive methods. Computational experiments were designed and performed to compare several production scheduling algorithms. Among various constructive heuristics considered, an algorithm called HENLL using an insertion logic showed the best performance. The proposed metaheuristic is based on the iterated greedy (IG) search method, and the results obtained demonstrated significant improvement compared to the heuristics alone. It is expected that this study may be used by production planning and control (PPC) professionals to apply the proposed method to schedule production more efficiently. We show that the proposed method successfully presented a better solution in relation to total tardiness, considering the above mentioned environment.

A flat Aluminum specimen with a geometric discontinuity, which allows testing of the applicability of 2D and 3D Digital Image Correlation Strain measurements, has been considered for this research since it is prone to high stress concentration via Addis Ababa Institute of Technology research interest. Experimental strain using digital image correlation and geometry measurements should be measured with estimated material properties and compare the results with theoretical model predictions. Aluminum plate with central hole were subjected for far field stress in the Machine shop of School of Mechanical and Industrial Engineering at Addis Ababa University in order to test the agreement between DIC’s strain analysis, strain gauge strain analysis and calculated empirical formulas of strain analysis and for the stress distribution of the plate elastically deformed by using VIC-3D and strain gauge. The aim is to measure vertical strain field, Vertical strain along horizontal line through hole center as function of applied loading and vertical strain using theoretical formula along same line as measurements in a plate with central hole subjected to far field and near field tensile loading using visual image coloration (VIC-3D) software, Destensometere device and solid mechanics equations to compare strain results.

Transnational producers facing the present-day competitive global supply-chain environments need to pursue the most appropriate manufacturing scheme, quality screening task, and stock shipping plan to satisfy customer’s timely multi-item requirements under minimum overall product fabrication-delivery expenses. This study develops a producer-retailer incorporated multi-item two-stage economic production quantity- (EPQ-) based system with delayed differentiation, expedited-rate for common parts, multiple deliveries plan, and random scrap. It aims to assist current manufacturing firms in achieving the aforementioned operating goals. Mathematical methods help us build an analytical model to explicitly portray the studied problem’s features and derive its overall system expenses. Hessian matrix equations and optimization approaches help us prove convexity and derive the cost-minimized fabrication- delivery decision. This study gives a simulated example to illustrate the research outcome’s applicability and the proposed model’s capabilities numerically. Consequently, diverse crucial information becomes obtainable to the manufacturers to facilitate various operating decision makings as follows: (i) the cost-minimized fabrication-delivery policy; (ii) the behavior of system’s overall expenses and operating policy regarding mean scrap rate, and different relationships between common part’s values and completion-rate; (iii) the system’s detailed cost components; (iv) the system’s overall expenses, utilization, and common part’s uptime concerning different common part’s expedited rates; and (v) the collective effects of critical system features on the overall expenses, uptime, and optimal cycle length, etc.