An Approach to Assess Sustainable Supply Chain Agility for a Manufacturing Organization

Worldwide business organizations realize that agility of sustainable supply-chain is a requisite need for survival in a dynamic, competitive, and unpredictable market. The contribution of this research is to explore and evaluate sustainable agility in supply chains for a dairy manufacturing organization located in Saudi Arabia. Other contributions of this research are to update the literature about the different factors contributing to achieve agile supply chain, propose conceptual framework and assessment approach incorporating the relationships between sustainable supply-chain capabilities, enablers, and attributes, and shortlisting the agility barriers and how they would facilitate manufacturing organizations’ performance. The paper presents supply chain agility evaluation approach, which covers identification of agile supply-chain capabilities and drivers. It also presents a conceptual model and a framework to define agility level and barriers within the supply-chain. In the paper, fuzzy logic approach is preferred, owing to its capability to incorporate and deal with problems involving impreciseness and vagueness phenomena. Threshold-value in this study for the case organization is set to 0.24829. The outcome of the adopted approach indicates that 21 attributes performed below the threshold value; these attributes are further categorized as agility barriers. These are the barriers within their supply chain that impact the agility-level. For the case organization, the foremost priority is to enhance maintainability and serviceability to make it flexible and inexpensive to establish an agile responsive supply chain. At the same time, it should have priority to focus on development and integration of their core competencies to deal with cross-functional and cross-enterprise issues in supply chain. For the case organization, the agility level was found “very agile,” although it is below the “extremely agile.” Thus, a study was developed to understand the behaviour of the supply chain agility and assess/evaluate it to support decision makers in order to develop a strategic solution for different organizational barriers

Statistical modeling of emergency medical services’ response and rescue times to road traffic crashes in the Kingdom of Saudi Arabia

Emergency medical services (EMS) is a critical component high-quality health-care. Road traffic crashes are one of the major causes of death and injury around the world. In the Kingdom of Saudi Arabia (KSA), the road traffic crash death rate has reached 29 per 100,000 people, or 11.25% of total deaths in 2018. The Saudi Red Crescent Authority (SRCA) is responsible for providing EMS in KSA. However, its average response time to road traffic crashes (14 min) is slower than the international standard (8 min). In this study, we analyzed a total of 57,928 road traffic crash reports recorded in 2019 by the SRCA for all cities in the KSA. The effective planning of SRCA, which is highly dependent on historical data analysis, is critical for decreasing emergency response times and, thereby, rescue times. Thus, we aimed to analyze response and rescue time trends related to road traffic crashes to identify significant factors that would assist decision-makers in enhancing the responsiveness of EMS through rescheduling, relocating stations, managing resources (e.g., ambulances and staff), or strategies based on the factors identified as significant. Statistical tools were used to identify the significant factors that affect the SRCA's performance in responding to road traffic crashes. The analysis results showed that the response and rescue times for road traffic crashes of the SRCA varied within as a result of different factors like geographical region, academic calendar, crash time, weather conditions, the severity of injuries sustained, and the number of injured people. The central regions have the longest average response and rescue times while the northern regions have the shortest ones. Response and rescue times were higher during daytime hours and holidays than during night hours and non-holiday periods. The results also indicated that EMS response and rescue times were significantly associated with mortality rate for road traffic crashes. As a result, by decreasing response and rescue times, the mortality rate for traffic accidents in the KSA could be decreased. Identifying and understanding significant factors that impact EMS response and rescue times can help decision-makers improve the performance of EMS, reduce response and rescue times, save people's lives, and reduce governmental healthcare costs.</p

Assessment of Supply Chain Agility to Foster Sustainability: Fuzzy-DSS for a Saudi Manufacturing Organization

Supply chain agility and sustainability is an essential element for the long-term survival and success of a manufacturing organization. Agility is an organization&rsquo;s ability to respond rapidly to customers&rsquo; dynamic demands and volatile market changes. In a dynamic business environment, manufacturing firms demand agility to be evaluated to support any alarming decision. Sustainability is an aspect to sustain collaboration, value creation, and survival of firms under a dynamic competitive business scenario. Agility is a capability that drives competitiveness to foster sustainability aspects. The purpose of this article is to consider and evaluate the supply chain behavior within the context of Saudi enterprises. The efficacy and relevance of this model were explored through a case study conducted in a Saudi dairy manufacturing corporation. Owing to the complexity and a large number of calculations that are required for evaluating the agility of the supply chain, a decision support system was proposed as a tool to assess the supply chain and identifying barriers to a strategic sustainable solution for a specific organizational target. The decision support system is extensive as it contains six separate agility enablers and ninety-three agility attributes for the supply chain. The assessment was carried out using a fuzzy multi-criteria method. It combines the performance rating and importance weight of each agile supply chain-enabler-attribute. To achieve and sustain local and global success, the case organization strove to become a major local and global manufacturer to satisfy its customers, reduce its time to market, lower its total ownership costs, and boost its overall competitiveness through improving its agility across supply chain activities to foster sustainability for a manufacturing organization located in Saudi Arabia

Comparison of Laser Milling Performance against Difficult-To-Cut Alloys: Parametric Significance, Modeling and Optimization for Targeted Material Removal

During laser milling, the objective is not always to maximize the material removal rate (MRR). Milling of new material with targeted MRR is challenging without prior knowledge and established sets of laser parameters. The laser milling performance has been evaluated for three important aerospace alloys, i.e., titanium alloy, nickel alloy and aluminum alloy using the response surface method experimental plan (54 experiments for each alloy). Parametric effects of five important laser parameters, statistical analysis (main effects, interaction effects, strength and direction of effects), mathematical modeling and optimality search is conducted for the said alloys. Under the non-optimized laser parameters, the actual MRR significantly varies from the targeted MRR. Variation in the aluminum alloy is at the top as compared to the other two alloys. Among other significant terms, three terms have the largest effect on MRR in the case of TiA, two terms in the case of NiA, and five terms in the case of AlA. Under the optimized sets of laser parameters, the actual material removal highly close to the desired level (100%) can be achieved with minimum variation in all the three alloys. Mathematical models proposed here have the capability to well predict material removal prior to the actual machining of Ti6Al4V, Inconel 718 and AA 2024

Achieving the Minimum Roughness of Laser Milled Micro-Impressions on Ti 6Al 4V, Inconel 718, and Duralumin

Titanium-aluminium-vanadium (Ti 6Al 4V) alloys, nickel alloys (Inconel 718), and duraluminum alloys (AA 2000 series) are widely used materials in numerous engineering applications wherein machined features are required to having good surface finish. In this research, micro-impressions of 12 &micro;m depth are milled on these materials though laser milling. Response surface methodology based design of experiment is followed resulting in 54 experiments per work material. Five laser parameters are considered naming lamp current intensity (I), pulse frequency (f), scanning speed (V), layer thickness (LT), and track displacement (TD). Process performance is evaluated and compared in terms of surface roughness through several statistical and microscopic analysis. The significance, strength, and direction of each of the five laser parametric effects are deeply investigated for the said alloys. Optimized laser parameters are proposed to achieve minimum surface roughness. For the optimized combination of laser parameters to achieve minimum surface roughness (Ra) in the titanium alloy, the said alloy consists of I = 85%, f = 20 kHz, V = 250 mm/s, TD = 11 &micro;m, and LT = 3 &micro;m. Similarly, optimized parameters for nickel alloy are as follows: I = 85%, f = 20 kHz, V = 256 mm/s, TD = 8 &micro;m, and LT = 1 &micro;m. Minimum roughness (Ra) on the surface of aluminum alloys can be achieved under the following optimized parameters: I = 75%, f = 20 kHz, V = 200 mm/s, TD = 12 &micro;m, and LT = 3 &micro;m. Micro-impressions produced under optimized parameters have surface roughness of 0.56 &micro;m, 2.46 &micro;m, and 0.54 &micro;m on titanium alloy, nickel alloy, and duralumin, respectively. Some engineering applications need to have high surface roughness (e.g., in case of biomedical implants) or some desired level of roughness. Therefore, validated statistical models are presented to estimate the desired level of roughness against any laser parametric settings