The resource-constrained project scheduling problem (RCPSP) is a well-known and widely studied topic. The underlying problem assumes that non-preemptions and that constant resources are restrictions imposed on project activities, which are to be scheduled, subject to precedence relation and limited resource constraints. Project activities, in RCPSP, are classified under category A. The problem is expanded to include various other activity assumptions categories, such as B and C. In the Preemptive-RCPSP, project activities are classified under category B, which refers to the activity that can be implemented using constant resources and constant durations. In the Flexible-RCPSP, project activities are classified under category C, which refers to the activities that can be executed using flexible resources over flexible durations, and preemptions are not allowed. However, in One-of-a-Kind Production companies (OKP), such as the housing industry, plastic injection moldings, and RV manufacturing, all known as “manufactured-to-order” operations, the activities are classified under category D in addition to A, B, and C, simultaneously. Category D refers to the activities that can be executed using flexible durations and flexible resources, and preemptions are allowed. In this paper, therefore, we present a new effective model in order to deal with the projects that consist of all the previous activity assumptions simultaneously to generate feasible project schedules. Case studies are included, and the results show that the resources usage is increased and the project makespan is reduced.

Servant Leadership is well known as an employee-oriented leadership style which is used by several major corporations. This work investigates the effects that Servant Leadership may have on the success of Information Technology (IT) projects. To estimate these effects via structural equation modelling (SEM) this study is based on already established models: the model of Servant Leadership developed by Van Dierendonck and Nuijten and the model of IT project success developed by Harwardt. Three of the Servant Leadership dimensions have positive impact on the success dimensions IT project. The Servant Leadership Dimension Accountability has a positive impact on the dimensions Project management success, Perception success and Result success. Authenticity has a positive impact on Project management success and Result success, whereas Forgiveness affects only Result success.

The Project Portfolio Selection is a complex process that involves many factors and considerations since the project is proposed until the project portfolio is finally selected. Project Portfolio Management is the iterative process of assessment, selection and implementation of projects, and the most important part of that is to select projects for portfolio where the or-ganization is required to identify and prioritize projects with the most objective alignment to its objectives. Since the selection of a suitable projects is very important, it is necessary to develop mathematical models to lead the organization towards the final goal. To achieve this goal, these models should reflect the organization's position, goals and priorities as much as possible. In this paper, we propose a multi - objective model for selecting the project portfolio that maximizes efficiency, quality while minimizes the risk involved in project execution.

In the past, due to the use of two-dimensional design, the probability of error in large projects increased. Over time, the need for a digital 3D model has increased in the lifetime of refineries, petrochemicals and power plants. Today, the editable digital 3D model is the basic needs of industrial plants. The Abadan Oil Refinery Co., due to its need for inspections and possible changes in the refinery, has also needed an editable 3D Digital Plant during the past few years. In this paper, with the development of a new methodology, the non-editable Navisworks® model of phase 1 and 3 of Abadan Oil Refinery was transformed into an editable Digital 3D model in AVEVA PDMS. In this methodology, the PDMS programming language called Programming Macro Language (PML) as well as .net code was used. Finally, using the Navisworks® model, these two phases, which consisted of 38 Areas, 2185 equipment, 17966 pipes, 7046 instruments, and 2617 structures were converted into an editable PDMS model for nine months.

This paper is aimed at reviewing present state of the art (1998-March 2019) on the impact of Enterprise Resource Planning (ERP) implementation in Small and Medium Enterprises (SMEs). It includes critical success factors and critical failure factors. The technique depends on writing survey for optional information gathering. It characterizes the expressions that are utilized to get explore papers from databases and advanced studies on the ERP implementation in SMEs. It additionally incorporates the consideration and prohibition criteria to im-prove nature of papers. At that point methodical audit is made on the accessible papers to research the effect of ERP usage in SMEs. Critical factors are identified for success and failure of ERP implementations and actual impact of the same on SMEs (add actual success and failure factors here besides impact). The research found in this paper has limitations in terms of the period of which research papers have been reviewed. An implicit limitation is that it does not consider an empirical study except focusing on the state of the art found in the re-search area. However, its insights will have potential benefits and the directions for future work. This paper contributes to the research on the impact of ERP implementation on SMEs either positively or negatively. It discovers critical success factors, critical failure factors and impact through secondary data collection method. The insights will help SMEs and stake-holders of SMEs and ERP service providers learn about the reasons for failure or success and take necessary course of action.

Lean Six Sigma is systematic and excellent operation management approach aimed to en-hance overall production through the elimination of waste and improve customer satisfaction. In the present case study, automobile part manufacturing unit has been selected and found 22% wastage in manufacturing steps resulting reduction in production. The primary objective of this research is to find the main reasons of production wastage and recommend corresponding remedies to counter the wastage reasons. For this purpose, Lean Six Sigma approach with the help of DMAIC methodology is implemented to observe and examine different root causes of the frame lugs production losses and rejection problems. The result reveals that the movement of material and employee are critical issues for wastage of resources, ultimately affecting production of industry. Lastly, the possible solutions are to be advised to tackling these issues. The successful execution of the proposed solutions show 7% growth in the production of the component which saves annually INR 15, 64, 056.

The application of material handling robots (MHRs) has been commonly observed in flexible manufacturing systems (FMS) for efficient material handling activities. In order to gain maximum throughput, minimum tardiness from the minimum investment of funds for the material handling activities, it is important to determine the optimum numbers of MHRs required for efficient production of jobs in the FMS. In the present work, the requirement of MHRs is optimized for different FMS layouts by using a heuristic procedure. Initially, a mathematical model is proposed to identify the MHRs requirement to perform the material handling activities in the FMS, later on, the model is optimized by simulating a novel heuristic procedure to find the required optimum number of MHRs in the FMS. The proposed methodology is found to be generic enough and can also be applied in various industries employing the MHRs.

Construction operations are blamed as one of important causes of green gas effects. During the past few decades, there has been tremendous efforts to reduce the negative effects of construction operations on environment. This paper presents an application of data envelopment analysis to measure the relative efficiencies of the researches accomplished by various countries around the world on green construction or green management. The study expects countries that produce higher amount of CO2 accomplish more quality research articles. To do this, the study performs a survey using three keywords; namely “green construction”, “green building” and “sustainable building” on Scopus database and found 8692 articles over the period 1965-2019 where one of these keywords, at least, was used in their abstracts, keywords or titles. We also use three measures of h-index, I-10 and total publications repre-sentative of quality and quantity of the outputs produced by researchers. The study considers 28 countries responsible for at least 90% of CO2 emission for measuring the relative efficiency program using data envelopment analysis. The results indicate that Hong Kong was the only efficient country followed by Singapore with relative efficiency of 0.67.

In this paper, a backward approach is proposed for maximizing net present value (NPV) in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF). The progress payment method is used and all re-sources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in backward mode. For this purpose, a Genetic Algorithm is applied to solve experimental cases with 50 variables and the results are compared with forward serial programming method. The remarkable results reveal that the backward approach is an effective way to maximize NPV in MRCPSP-DC while activity splitting is allowed. The algorithm is flexible enough to be used in real project.

Maintenance engineering plays an important role in management of oil and gas projects. This paper presents a dynamic programming approach for resource allocation in oil and gas projects. The study presents a dynamic programming approach to allocate human resources for repairment of oil and gas equipment. Many heavy equipment normally needs to be repaired on predetermined scheduled and the process normally takes days or even weeks. The process can be divided into three stages of disassembling the equipment, executing the repairment and assembling the equipment. The proposed model of this paper models the problem into a classical dynamic programming and using a real-world case study, the implementation of the proposed model is described.