International Journal of Research in Industrial Engineering
Volume:11 Issue: 3, Summer 2022

During my travel to the research case industry to advice internship placed students of our university, I have communicated with company owners that there is a problem related with productivity measurment andimprovement.   So that we have decided to assess the overall productivity of the company with the considertaions of potential sub systems with in it. The existing system overall productivity level have been measured through Performance Objectives Productivity (PO-P) approach. In the case company six subsystems where identified: technology, production, marketing, ergonomics, values and goals and materials. Afterwards, their importances to the company have been prioritized using paired comparison analysis technique.  By using Pareto analysis; technology, marketing, ergonomics and production have been identified as potential subsystems. By using PO-P approach the productivity of these four potential subsystems has been measured. As a result, productivity indices of production, marketing, technology, and ergonomics subsystems are 0.7379, 0.6661, 0.7882 and 0.7156 respectively. This resulted the existing system overall productivity of 0.652.

Entrepreneurial teams significantly influence the growth, profitability, and innovation of new businesses, specifically in Information Technology (IT) start-ups. However, there is limited knowledge about the impact of personal characteristics of entrepreneurial team members and their social interactions on the success of their business. This paper explores the effect of entrepreneurial team characteristics and their social interactions on the success of IT start-ups. The study employed a quantitative research design and data from 213 entrepreneurial teams in IT start-ups. The findings showed that heterogeneity, experience, self-efficacy, commitment, trust, and social interactions of entrepreneurial team members have a significant positive influence on the success of IT start-ups. Implications of the findings for policy, practice, and research development are discussed.

Internet-based financial systems and communications have entered a new phase with the advent of blockchain technology and cryptocurrencies. The new economic system with its transparency, privacy, and peer-to-peer networking, has attracted the attention of economists. The advent of cryptocurrencies has brought new blood into the veins of blockchain technology and accelerated its growth. After a decade of cryptocurrency lifetime, it is necessary to identify key components to develop the use of this technology. The aim of this study is to identify the indicators needed to develop the use of blockchain technology and cryptocurrencies in financial systems. A total of six indicator groups were identified including technology, legislation, cybersecurity, regulatory methods, public acceptance, and investment. For this purpose, the three-round Delphi study is used to elicit expert opinions. Calculation of Kendall’s W coefficient shows a high degree of concordance of experts' opinions in determining the indicators. The indicators presented in this research can be a helpful guide for governments and economic sections to develop the use of blockchain technology in financial systems.

One of the fields studied in the science of heat physics is the thermoelectric phenomenon. This phenomenon is in fact the interaction between the current of electricity and the thermal properties of a system. In simpler terms, it is a phenomenon in which the direct conversion of a temperature difference to voltage occurs. In this paper, we introduced a method based on the finite difference technique for solving a fractional differential equation in the field of thermal physics which describes the thermoelectric phenomena, numerically. For this purpose, we used fractional order derivatives with the definitions of Caputo, finite differences with the second order central finite-difference approach, and the first order central finite-difference. By using this method, we translate the desired differential equation to a system of nonlinear differential equations which can be solved. Finally, some numerical are used to demonstrate the effective and accuracy of the scheme. The obtained numerical results show that our proposed method is highly accurate.

In this paper, a two-stage model is designed for arranging and locating vehicle routes with simultaneous pickup and delivery. The model developed in the first stage optimizes the arrangement of products in packages and thus optimizes packages' length, width, and height for delivery to customers. In the second stage, the goal is to provide customers with vehicle in simultaneous pickup and delivery. In this part of the model, the location of distribution centers is potentially considered, and the demand and cost parameters are considered uncertain. To solve the problem, precise methods and meta-heuristic algorithms of PSO for the first stage and multi-objective meta-heuristic algorithms NSGA II and MOALO for the set have been used. The results of examining the efficiency of the algorithms in the second stage show the high efficiency of the MOALO algorithm with a valuable weight of 0.8388. Therefore, to implement the model in the real problem (Golrang Broadcasting Company), the MOLAO algorithm has been used, the management results include obtaining 15 efficient answers.

Sequencing and scheduling are the forms of decision-making approach that play a vital role in the automation and services industries. Efficient scheduling can help the industries to achieve the full potential of their supply chains. Conversely, inefficient scheduling causes additional idle time for machines and reduces productivity, which may escalate the product price. This study aims to find the most effective algorithm for solving sequencing and scheduling problems in a non-preemptive flow shop environment where the objective functions are to reduce the total elapsed time and idle time. In this research, four prominent exact algorithms are considered and examined their efficiency by calculating the ‘total completion time’ and their goodness. In order to demonstrate the comparative analysis, numerical examples are illustrated. A Gantt chart is additionally conducted to exhibit the efficiency of these algorithms graphically. Eventually, a feasible outcome for each condition has been obtained by analyzing these four algorithms, which leads to getting a competent, time and cost-efficient algorithm.

Mindset means mental attitude. Methodology means a system of methods used in a particular area of study. If one studies any textbook in industrial engineering, one reads about various optimization methods. Hence it is natural to assume that industrial engineering is a methodology. However, this paper argues that industrial engineering is a mindset geared toward optimisation, and methodology is just a manifestation of that mindset.