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According to the authors research, Agile approaches are increasingly being deployed successfully alongside phase-gate processes in engineering and R&D functions outside software, with a very positive result.

An Agile approach to product development has been a mainstay of the software industry since the turn of the century. In recent years, some non-software product-based companies have successfully combined both Agile and non-Agile methods in a complementary way to pursue breakthrough innovation. The article reports on how to make this combination work.

The study found companies adopting two general approaches when trying to introduce Agile into an existing phase-gate process: integrating Agile into a single innovation process or adding a partly parallel Agile path.

As a measure of Agile’s potential, the software industry has consistently produced patents at three times the level of the next-most prolific sectors.

Arthur D. Little’s research reveals that companies that have successfully added Agile methods to their toolboxes and tailor their innovation approaches by the type of innovation – incremental or breakthrough–perform significantly better than those that stick to single phase-gate approach.

The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength development. This study aims to predict the compressive strength of normal concrete and high-performance concrete using four datasets.

In this paper, five established individual Machine Learning (ML) regression models have been compared: Decision Regression Tree, Random Forest Regression, Lasso Regression, Ridge Regression and Multiple-Linear regression. Four datasets were studied, two of which are previous research datasets, and two datasets are from the sophisticated lab using five established individual ML regression models.

The five statistical indicators like coefficient of determination (R²), mean absolute error, root mean squared error, Nash–Sutcliffe efficiency and mean absolute percentage error have been used to compare the performance of the models. The models are further compared using statistical indicators with previous studies. Lastly, to understand the variable effect of the predictor, the sensitivity and parametric analysis were carried out to find the performance of the variable.

The findings of this paper will allow readers to understand the factors involved in identifying the machine learning models and concrete datasets. In so doing, we hope that this research advances the toolset needed to predict compressive strength.

Food and grocery, which accounts for around 60% of the overall retail market in India, is the most promising area for launching a retail firm. The objective of this research paper is to conduct a thorough investigation of the impact of customers’ geographic, demographic and psychographic characteristics on the selection of retail store format choice behavior in the quickly growing Indian food and grocery retail industry, also to analyze the mediating role of store image on the store choice behavior.

A descriptive research design is used to collect data using the survey method and a structured questionnaire. The data collected from more than 400 food and grocery retail customers from neighborhood Kirana stores, supermarkets and hypermarkets in Karnataka, India, would be analyzed using both descriptive (mean and standard deviation) and Structural equation modeling (SEM) techniques. SEM techniques are used for validation of the model with independent constructs namely Demographics factors, Socio-Economic factors, Geographic factors, Lifestyle and Shopping Motives, a Mediating variable Store Image, and a dependent variable Store choice behavior. Partial least squares structural equation modeling (PLS-SEM) is used to examine the suggested theoretical framework.

The model is tested to reveal the impact of shoppers’ age, gender, occupation, education, monthly household income, family size, and distance traveled to the store, which all play a role in their retail format choice. Also, the socio economic and life style factors of shoppers influence their purchasing decisions as well; store image partially mediates between customer characteristics and store choice behavior.

The study has practical implications for food and grocery retailer in understanding customer behavior in the context of changing customer demographic and psychographic features in the Indian retailing sector. The findings aid retail merchants, allowing them to develop more successful retail marketing strategies and gain a competitive advantage.

This study could serve as a springboard for future research in this field. Retail marketers will benefit from the findings in terms of format creation and reorientation of marketing strategies in the shortest time.

This study highlights the demand for low-cost and high accuracy products through the design and development of new 3D printing technologies. Besides, significant progress has been made in this field. A comparative study helps to understand the latest development in materials and future prospect of this technology.

Nevertheless, a large amount of progress still remains to be made. While some of the works have focused on the performances of the materials, the rest have focused on the development of new methods and techniques in additive manufacturing.

This paper critically evaluates the current 3D printing technologies, including the development and optimizations made to the printing methods, as well as the printed objects. Meanwhile, previous developments in this area and contributions to the modern trend in manufacturing technology are summarized briefly.

The paper can be summarized in three sections. Firstly, the existing printing methods along with the frequently used printing materials, as well as the processing parameters, and the factors which influence the quality and mechanical performances of the printed objects are discussed. Secondly, the optimization techniques, such as topology, shape, structure and mechanical property, are described. Thirdly, the latest development and applications of additive manufacturing are depicted, and the scope of future research in the relevant area is put forward.

This paper aims to investigate the effects of various heat treatments on microstructure, hardness, porosity and corrosion properties of the parts.

Hot isostatic pressing (HIP) process, various heat treatments and their combinations were applied to the AlSi10Mg parts produced by direct laser metal sintering (DMLS).

It has been found that the HIP process, which is a post-processing process, reduces the amount of porosity in DMLS-AlSi10Mg material, thus improves corrosion resistance significantly.

In this study, the HIP process and subsequent T6 heat treatments were applied to AlSi10Mg parts produced by the DMLS technique. The study aims to increase the corrosion resistance of AlSi10Mg parts by reducing porosity with the HIP process and by altering the microstructure with the T6 process.

The purpose of this paper is to design a quadrotor with collective morphing using the simultaneous perturbation stochastic approximation (SPSA) optimization algorithm.

Quadrotor design is made by using Solidworks drawing program and some mathematical performance relations. Modelling and simulation are performed in Matlab/Simulink program by using the state space model approaches with the parameters mostly taken from Solidworks. Proportional integral derivative (PID) approach is used as control technique. Morphing amount and the best PID coefficients are determined by using SPSA algorithm.

By using SPSA algorithm, the amount of morphing and the best PID coefficients are determined, and the quadrotor longitudinal and lateral flights are made most stable via morphing.

It takes quite a long time to model the quadrotor in Solidworks and Matlab/Simulink with the state space model and using the SPSA algorithm. However, this situation is overcome with the proposed model.

Optimization with SPSA is very useful in determining the amount of morphing and PID coefficients for quadrotors.

SPSA optimization method is useful in terms of cost, time and practicality.

It is released to improve performance with morphing, to determine morphing rate with SPSA algorithm and to determine PID coefficients accordingly.