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Machine Learning Algorithms for Industry Using Image Sensing
Published in Punit Gupta, Dinesh Kumar Saini, Rohit Verma, Healthcare Solutions Using Machine Learning and Informatics, 2023
Aakash Dhall, Hemant K Upadhyay, Sapna Juneja, Abhinav Juneja
Vital issue with the growing number of Internet of Things devices is the enhanced complication needed for their safe operation. The enhance complication generates safety problems that are much more challenging than the complex challenges individuals encounter when protecting a unit. We focus few negative issues caused by intelligent systems and collected devices, and discuss the problems connected to safety, privacy, and utility are inextricably linked, and factors those focus all the four at the same time are required. Individual system safety and security requirements based on current technologies are required. Similarly, future implementations of such systems must be driven by technology which defines for the individuals for appropriately handling collecting devices.
Safety management anno 2016
Published in Erik Hollnagel, Safety-II in Practice, 2017
The development of many of the new technologies had been, to a large extent, driven by the needs of the military during WW-II and its continuation in the Cold War that followed. The precursor to industrial safety management systems (SMS) was the concern for system safety engineering that began in the 1950s in the U.S. Air Force Ballistic Missile Division. The increased complexity of the equipment created a need to ensure that technology would function as intended with optimum safety within the constraints of operational effectiveness. The same need could soon be found in the civilian sector where complex technologies were enthusiastically greeted as a way to provide better products and services to the consumer as well as higher profitability. Despite the many problems that this has led to, with regard to safety as well as other aspects, these needs have so far shown little sign of weakening.
System Improvement
Published in Lesley Baillie, Elaine Maxwell, Improving Healthcare, 2017
Elaine Maxwell, Lesley Baillie, Jerusha Murdoch-Kelly
Hollnagel et al. (2013) described systems safety management as falling into two categories: Safety-I and Safety-II: Safety-1 is the absence of actual accidents or incidents and it assumes that the system can be studied in constituent parts. It also assumes that safety is a binary construct: it is either present or absent with no grey areas. This does not recognise the latent risks that Reason's Swiss cheese model addresses and the absence of incidents may be due to luck rather than design. Slight changes to the system may weaken the defence barriers and a catastrophic accident may occur. Safety-1 may be somewhat like playing Russian roulette: the hazard may not be realised in the first five shots but the bullet was always there.Safety-II approaches are prospective and a system is deemed safe if it can adjust to change within the system, that is, if it can demonstrate resilience. The focus is not on demonstrating causation of past incidents, but understanding the conditions that make things go right: what makes a system resilient.
A fuzzy causal relational mapping and rough set-based model for context-specific human error rate estimation
Published in International Journal of Occupational Safety and Ergonomics, 2021
Suprakash Gupta, Pramod Kumar, Gunda Yuga Raju
The proposed model is capable of capturing the embedded uncertainty in data and subsequent classifications. It estimates the HER with reasonable accuracy that can be readily used to assess the safety status of a mine or any system. The safety scenario and HER of a mine can be predicted after the CDF status is evaluated. The error rate for different types of error in various mining activities will guide mine management to develop interventions. This will implement a future course of action for enhancement of safety and achieving the target of zero fatalities and lost-time accidents. The proposed model may be used to verify the adequacy of the ongoing safety enhancement programme. It could prove to be a guiding tool for management to address the shortcomings in safety-related issues. It will help in decision-making and implement effective control and remedial measures for enhancing system safety. The problem of experimental and observational data limitation can be managed successfully through retrospective analysis. The developed model can guide the prospective analysis. This method is based on the error type of a generic nature that removes industry-specific domain restrictions. However, the validity of the results depends heavily on the experts’ judgements and their beliefs and knowledge about human error. Judicial selection of experts and a large volume of accident data will fine-tune the reliability of the results. The refinement of the set of CDFs will increase the model’s credibility and applicability domain.
Hazard analysis using a Bayesian network and linear programming
Published in International Journal of Occupational Safety and Ergonomics, 2020
Burak Efe, Mustafa Kurt, Ömer Faruk Efe
Firms are obliged to provide a safe work environment for their employees due to law requirements. Employees can work more comfortably when firms establish a safe work environment. Thus, productivity can be increased. It is highly probable that an occupational accident occurs in an unsafe work environment. Occupational accidents can result in injury or death. This situation can lead to loss of the labor force, loss of productivity and paying compensation. For these reasons, firms must take all necessary precautions. Hazard assessment is needed to establish a safe work environment. The managers and all employees must attend to their implementation. The important result of this article is that the hazards of the related processes in the firm are ranked according to hazard level. If these hazards are considered correctly, the work environment could be improved in terms of occupational safety. The hazards in the work environment can interact with each other. Namely, the occurrence probability of a hazard can increase or decrease the occurrence probability of another hazard. The managers can examine the dependencies of events, updating probabilities and dealing with vagueness using a Bayesian network. This article handles the capacity of the firm to make an occupational health and safety policy so that the managers can use this policy in the long term. It presents managers with more beneficial and effective information in real-life practices such as determining the priorities of the hazards, allocating necessary resources to the hazards properly and establishing an occupational health and safety policy for improving system safety. It significantly ensured awareness among the employees and managers toward implementation of a Bayesian network.
Evidence-based evaluation of safety management in port labor outsourcing
Published in International Journal of Occupational Safety and Ergonomics, 2023
Wenchao Wang, Fayi Huang, Jingjing Wang
In this study, the focus was on labor service enterprises that provide services for port enterprises. They comprised more than 10 labor service companies that delivered services, as well as a port group corporation that provided services for contractors. The varieties generated from services are generally consistent across companies, mainly concentrated in port loading and unloading production. Examining companies alike in this regard provided more evidence data compared to studying safety accident cases, as the research method allowed for evaluation to be made between the companies and regulatory standards. In addition, the study concentrated on the reformation outsourcing of port service innovations, as well as the practices designed to improve the existing production services. Evidence-based evaluation design was selected because port enterprises rarely develop new outsourcing businesses, while the current mode of port production has continued to this day. Further, focusing on an untraceable empirical evaluation of the status quo would have yielded only a detached view of the reality of outsourcing improvement. Moreover, evidence-based evaluation is based on the best evidence provided by researchers and the practice guidelines and standards formulated by managers. Based on the evidence, the research evidence is classified according to the scientific degree of the methods used, the evidence database is established and the relationship between relevant parties is communicated. Then, the researchers developed guidelines and standards to evaluate evidence-based practices based on the best evidence selection methods. That is, based on the system safety risk identification and evaluation results, they analyzed the causes of system safety management problems and formulated a system safety management plan. The study design is shown in Figure 2.