Linear Programming Optimization Techniques for Addis Ababa Public Bus Transport

Anbessa City Bus Service Enterprise (ACBSE) is the only public enterprise that provides transport services in the city of Addis Ababa. The enterprise uses a fixed bus schedule system to serve passengers in more than 125 routes. However, the current bus assignment and scheduling system are becoming a challenge in the company’s operational performances. The objective of this paper is to develop an optimum bus assignment method using linear programming (LP). After a thorough analysis of the existing bus scheduling system, the LP model is developed and used to determine the optimal number of busses for each route in four shifts. The output of the LP-model is then validated with the performances of the existing systems. The findings of the study showed that the new model reveals better performances on the operating costs, bus utilization, and trips and distance covered compared with the existing scheduling system. The bus utilization is improved by the new system and cut costs on the one hand and improves the service quality to passengers on the other hand. The authors recommended the enterprise to adopt the new bus assignment system so that busses can be assigned based on the demand distribution of passengers for each route at a given shift.

Automotive Industrial Supply Chain Performance Evaluation under Uncertain Constraints on Cloud Computing System

Performance evaluation is a critical and complex task as well as uncertain demands for automotive supply chain. Several methods are applied and adopted to deal with current situations and maintain competitiveness such as fuzzy logic, neuro fuzzy, agent (multi) based evaluation, etc. However, such systems are not rapid enough to respond customer requirements by real-time on mobile cloud computing system. There are many companies that operate under the first tier company as subcontractors on the same goal. Cloud computing system is capable to monitor real-time production processes for every subcontractor to assist the 1st tier to make decision and respond customer effectively. Daily monitoring data of all subcontractors in the supply chain are stored in the central database and finally the performance evaluation can be done. The implication is cost reduction of the whole supply chain and increase competitiveness as well as continuous process improvement for all.

Exploring the Project Risk Management: Highlighting the Soft Side of Project Management

The majority of the approaches to managing project risk follow the logic of process groups. Project Management Institute (PMI) has 29 tools and techniques related to risk management process groups. Consequently, engineering and business schools have been accused of educating managers with sharp analytical skills but little understanding of social problems. The literature suggests that too much attention is focused on learning the techniques and formalities of risk management but not enough on the advanced issues of management. Also, the literature argues that there are two approaches to project management (hard and soft). The hard side only covers part of the managerial aspects which helps to manage foreseeable uncertainties. However, unforeseeable uncertainties need skills that related to soft side approaches such as emotional intelligence, navigating the organization’s culture, risk attitude, participative leadership style, and managing the relationship with stakeholders. This study provides an intensive review of the literature to discuss the need for integrating the hard and soft sides of management to achieve an effective risk management process. In addition, it proposes a conceptual framework that provides guidelines to enhance overall risk management efficiency.

Impact of ICT to Improve of the Manufacturing in a SME Biomedical of Mexicali, Mexico

This work presents a way to optimize the manufacturing processes in a small biomedical industry considered in the micro-, small-, and medium-sized enterprises (SME) group and located in the Mexicali city, using a specialized software that act as design and test of a new model, being the COSIMIR (Cell Oriented Simulation of Industrial Robots) software. With this software was designed a new industrial process in a workstation separated of the main step of a manufacturing line, where are fabricated biomechanical knees pads. The process was made as a manual activity in a work station and had to be separated from the conveyor belt of the main activities, because where previously made by an automatized device that was failing continually and was delaying the delivery to the next steps of the manufacturing processes and to the customers as a final product fabricated in this industry. In this place of the company, an operation was made to organize the biomechanical knee in a plastic container with divisions and to be transported safe and quickly to other area by a conveyor belt with linear process flow. The investigation was conducted from 2018 to 2019.

Weapon Target Assignment

This chapter is mainly based on an important sector of operation research-weapon’s assignment (WTA) problem which is a well-known application of optimization techniques. While we discuss about WTA, we need some common terms to be discussed first. In this section, we first introduce WTA problem and then we present some prerequisites such as optimization model, its classification, LP, NLP, SP and their classifications, and applications of SP. We also discuss some relevant software tools we use to optimize the problems. The weapon target assignment problem (WTA) is a class of combinatorial optimization problems present in the fields of optimization and operations research. It consists of finding an optimal assignment of a set of weapons of various types to a set of targets in order to maximize the total expected damage done to the opponent. The WTA problem can be formulated as a nonlinear integer programming problem and is known to be NP-complete. There are constraints on weapons available of various types and on the minimum number of weapons by type to be assigned to various targets. The constraints are linear, and the objective function is nonlinear. The objective function is formulated in terms of probability of damage of various targets weighted by their military value.

Industrial Safety Management Using Innovative and Proactive Strategies

Safety is considered a top priority due to its significance in safeguarding human lives and properties, especially in high-risk industrial sectors such as aviation, oil and gas, construction, transportation, steel manufacturing, and mining industries. These industries are plagued by workplace injuries, illnesses, and fatalities because of the dangerous work environments. As such, it is very vital to integrate safety into every work process in any industrial environment just like quality is built into products and services. It is important to establish and execute an effective safety management system to prevent the risks of irreversible accidents. This chapter begins with a background to safety management in industrial engineering and a discussion of the various issues of industrial safety management. It follows with an extensive description of existing and commonly used safety performance measurement methods. Several case studies are used to explain the methods and explore the important application areas relevant to most industrial sectors. The techniques and tools for safety data collection, analysis, and sharing are introduced together with their applications for safety management. The last section explains how emerging technologies can be implemented in most industrial sectors to enhance safety management.

Fuzzy Monte Carlo Simulation to Optimize Resource Planning and Operations

Resources planning and operations are essential concerns and specialty areas within industrial engineering and project management. Crew configuration plays a significant role in resource planning and operations. Crew configuration inefficiency is one of the most common reasons for the low productivity of manpower. Resources planning contains some inherent uncertainties and risks because it is an estimate of unknown values. Many factors affect resource planning. Some of these factors are fuzzy variables such as expert’s judgment, and some of them are random variables such as direct cost of equipment. The objective of this chapter is to present a method that combines fuzzy logic and Monte Carlo simulation (MCS) for the selection of the best crew configuration to perform a certain task. The model presented in this chapter is a joint propagation method based on both the probability theory of MCS and the possibility theory of fuzzy arithmetic. The research outcomes indicate that the presented model can reduce the duration and cost of a certain task, which will help reduce the cost and duration of the project.

Integrated Lean-Green-Six Sigma Practices to Improve the Performance of the Manufacturing Industry

To survive in the global competitive market, the manufacturing organization must adopt changes in technologies and strategies into their processes on a continuous basis. So, nowadays, Lean, Green, and Six Sigma became business process strategies, which are employed in most of the organization to enhance their manufacturing performance. However, the significant information is that these strategies are implemented sequentially instead of simultaneously. The objective of this chapter is to propose an integrated Lean- Green-Six Sigma strategic framework for manufacturing industries that effectively implementing this approach will lead business processes to achieve operational, financial, social, and environmental growth. This will also guide the practitioner and academician those who are working on manufacturing strategies.

A Hybrid Human-Data Methodology for the Conception of Operational Performance Management Systems

To excel in the overall business performance, daily processes and activities connected to produce a good or service need to be outperformed. Even though there is extensive literature on performance management and performance management systems, there is still no consensus over the conceptual model of such systems, in what is designated as Operational Performance Management Systems (OPMS). This chapter proposes a new approach to conceive feasible and desirable OPMS tools to assist managers on controlling and responding to operational needs, by combining Design Thinking (DT) and Data Analytics (DA), that provide holistic and deep business knowledge, as well as a data-driven based management. The authors conduct an empirical application through a case study within the context of a European airport’s Baggage Handling System (BHS). The case study procedure follows the proposed methodology’s stages, where the authors construct the problem space with a wide array of collected data, along with the solution exploration and refinement.

A Service Management Metric with Origin in Plant Management

The discipline of industrial engineering (IE) was originated in the US by Frederick W. Taylor, who first applied what he termed scientific management to machine shop management in the 1880s. IE expanded world-wide with applications of work measurement to all manner of manufacturing, then to services. A century later, as the Japanese practice of Total Productive Maintenance (TPM) became known in the US, the associated equipment management metric Overall Equipment Effectiveness (OEE) became well-known as a production metric that could be applied to individual manufacturing machines, production lines, and the overall production system. In this chapter, illustrations of the calculation of OEE are provided, along with modification of the three OEE inputs (availability, performance efficiency, and quality rate) to create a new service management metric Overall Service Effectiveness (OSE). Definitions and measures of service quality are reviewed. The first published application of OSE was to a city public transportation system, and is reviewed as a prototype. Essentially, applications of OSE require the industrial engineer to define service-specific measures of availability, processing rate, and quality at the management’s level of interest: work station, process, or system. The data collected to calculate OSE will also point toward actions that would improve OSE.