Asset health management plays a role in safety, reliability, and cost in the oil and gas industry. Health management requires considering human reliability since it affects asset health. Indeed, human reliability factors are considered carefully during the facility’s design phase but rarely during operation. Therefore, identifying these factors during operation helps to prevent incidents. This article presents research on the impact and role of human reliability in oil and gas operations. Human Reliability Assessment (HRA) methodology is used to understand human error in practice, including human reliability estimation using the Human Error Assessment and Reduction Technique (HEART) and Fault Tree analysis (FTA). A deep investigation of a real case study from Oman’s oil and gas industry, including interviews and questionnaires, is used to prove the concept. The real case study shows a 3.3

One of the most common sources of emissions and greenhouse gases (GHG) in the oil and gas industry is fired-based equipment, which needs to be minimized and mitigated to improve sustainable manufacturing systems. Local regulations provide allowable limits for GHG, which must be complied with. This study proposes a health index (HI) based emissions-monitoring system. The proposed HI quantifies the condition of the equipment's environmental efficiency to take corrective actions and improvement decisions. Also, the HI can be used as a national benchmark for regulation and improvement measurement purposes. A case study was applied to test the approach of a new health index in one gas plant in Oman, taking a stationary combustion steam boiler. The results show a good presentation of indices for each condition of GHG and the overall Health index for the equipment, which supports corrective actions.

Emad Summad has a PhD in Industrial Engineering.He is specializing on policy issues

Innovation ecosystems are classified as one of the complex economic systems where many parties with different interests are involved.The holistic objective of such alignment of entities is to cooperate in the creation of innovative outputs.The innovation ecosystem provides the environment for large corporates, entrepreneurs, investors, and governmental institutions to accumulate their sole offering into value capturing via networking and exchanging knowledge and expertise.Thus, such kind of ecosystem exhibits multiple partnerships and interactions among actors to fulfill their own needs and contribute to the value co-creation process.This paper explores the nature of innovation ecosystem as a set of networks comprising a large spectrum of agents interacting with each other.Most of the previous work on ecosystems has pursued qualitative studies emphasizing on how to orchestrate an innovation ecosystem entirely.However, we addressed such a phenomenon by means of an agent-based modeling considering both the micro level of the system which consists of the individual agents and the macro level which is represented by the aggregating of individuals' behaviors.The model can be used as a decision-making tool to examine the validity of an orchestrating strategy by detecting its dual impact on individual agents and on the overall performance of the ecosystem.

Emergency department (ED) is a complex system that falls under the category of acute healthcare institutions where health services are provided intensively regardless of the unknowingness of the severity of the medical cases and their spontaneous arrivals. Accordingly, developing a simulation model that exhibits the incurred interactions in ED will lend a hand in supporting the management of the ED in dealing with all those uncertainties. The model performs as a decision-making tool addressing the randomness nature of such an environment. Agent-based modeling simulation was preferred to model the interaction of ED elements using a computer language called Netlogo. And this selection was agreed upon after considering several literature reviews. The ED of Sultan Qaboos University Hospital was monitored, and the medical staff was also interviewed too to gain the required information to build up the model. A conceptual model of the ED was formulated Then, a simulation model was developed.

In this paper we present a decision analytic to analyze different product development scenarios and obtain the optimal recommendation on the product development time. These scenarios differ in many aspects such as the product complexity level, the competitor's quality level, price demand-sensitivity. The objective to generate managerial insights on how much time should a company spent in the development when theses market characteristics differ. In general, product development time is sensitive to this market and yet the optimal strategy varies.

Agent-Based Modelling and Simulation (ABMS) has increasingly been applied in diffusion of innovation research. The ABMS method is successfully implemented to different domains in business networks to study the diffusion of their innovation activities. This research therefore applies such ABMS method to a case company at Muscat, Oman with the objective to study the diffusion of its innovation activities to the public. The case company is a famous real-estate company in Oman, where it successfully diffused its innovative project to the public by using ABMS method. The results from the ABMS method were analyzed by using a common used platform like MATLAB MathWorks software. This is an ongoing research and this paper presents the initial results from the model. Since the acquirement of data took too long for this specific project, the incorporation of real world data and validation and adaption of the model are tasks for further research.