Industrial Safety Engineering Research Articles

A Study on a Knowledge Graph Construction Method of Safety Reports for Process Industries

There are some representative reports in industrial safety engineering, such as the Hazard and Operability Analysis and Pre-Hazard Analysis; however, a large amount of industrial safety knowledge in the report has not been fully explored. In order to reuse and release the value of industrial safety knowledge, this paper constructs a new industrial safety knowledge extraction framework. The framework combines the asset management shell to summarize the knowledge concept entities of machine description language and model description language. According to the safety report template, the framework also constructs a new industrial safety knowledge-mapping standard structure. Specifically, firstly, considering that the knowledge structure of safety reports is different in different processes of the process industry, this paper innovatively proposes a general industrial safety knowledge-mapping standard structure, which provides a practical solution for the integration of industrial knowledge representation problems in different processes. Secondly, based on the research progress of named entities, this paper presents an industrial named entity extraction method (INERM) for the process industry. This method designs an entity weight model to calculate the entity weight of each sentence, and adds part-of-speech weight to improve the entity extraction algorithm, which alleviates the problem that the existing entity extraction methods cannot reasonably use the semantic information and context of word. Finally, we construct a triple of industrial safety knowledge based on the rules and store it in Neo4j. In this paper, four semantic-type templates and five semantic relation templates are constructed based on the new industrial safety knowledge map standardization construction process of the process industry. The comparative experiments show that the accuracy of the INERM on the test set is improved by 17 percentage points on average compared with other key entity extraction algorithms. A total of 1329 entities are constructed in the directional application example of the fluid transportation process, which provides a large number of references for the safety of the fluid transportation process and is more conducive to improving the safety guarantee of the fluid transport process.

A novel knowledge graph development for industry design: A case study on indirect coal liquefaction process

Hazard and operability analysis (HAZOP) is a remarkable representative in industrial safety engineering. However, a great storehouse of industrial safety knowledge (ISK) in HAZOP reports has not been thoroughly exploited. In order to reuse and unlock the value of ISK and optimize HAZOP, we have developed a novel knowledge graph for industrial safety (ISKG) with HAZOP as the carrier through bridging data science and engineering design. Specifically, firstly, considering that the knowledge contained in HAZOP reports of different processes in industry is not the same, we creatively developed a general ISK standardization framework, it provides a practical scheme for integrating HAZOP reports from various processes and uniformly representing the ISK with diverse expressions. Secondly, we conceive a novel and reliable information extraction model based on deep learning combined with data science, it can effectively mine ISK from HAZOP reports, which alleviates the obstacle of ISK extraction caused by the particularity of HAZOP text. Finally, we build ISK triples and store them in the Neo4j graph database. We take indirect coal liquefaction process as a case study to develop ISKG, and its oriented applications can optimize HAZOP and mine the potential of ISK, which is of great significance to improve the security of the system and enhance prevention awareness for people. ISKG containing the ISK standardization framework and the information extraction model sets an example of the interaction between data science and engineering design, which can enlighten other researchers and extend the perspectives of industrial safety.

Quality and Metallic Pollution Level in Surface Waters of an Urban Industrialized City: A Case Study of Chittagong City, Bangladesh

P { margin-bottom: 0.21cm; direction: ltr; color: rgb(0, 0, 0); line-height: 107%; widows: 2; orphans: 2; }P.western { font-family: Times New Roman,serif; font-size: 12pt; }P.cjk { font-size: 12pt; }P.ctl { font-size: 12pt; } Abstract Disposal of urban and industrial waste is one of the major problems and responsible for both soil and water pollution in Chittagong city, Bangladesh. Total 22 surface water samples were collected from different locations of Chittagong city to assess quality and metallic pollution level. The concentrations of Fe, Mn, Cu, Cr and Pb in water samples ranged from trace- 10.37, trace- 1.91, 0.824–0.999, 0.11–1.32 and 1.69–2.56 µg ml -1 , respectively while the contents of Zn and Ni were trace. Among the metals, Pb was dominant in water samples followed by Cu and Cr. The study results inferred that all water samples were unsuitable for irrigation due to higher concentrations of Pb, Cu and Cr. Furthermore, Cr and Pb showed highly significant positive correlation, which indicates that the metals were interrelated with each other and may be originated from the same source of the study area. The mean concentrations of Ca, Mg, Na and K in water samples were 61.98, 77.08, 102.90 and 146.90 µg ml -1 , respectively. Among the anions, Cl contributes 98% to the total anionic mass balance followed by HCO 3 (1.84%). In respect of K, Cl and HCO 3 contents, all water samples were found unsuitable for irrigation. The study results concluded that surface water in the study area was significantly contaminated and hence the authority should take initiative to preserve the city environment. Keywords : Heavy metal, surface water quality, pollution, Chittagong, Bangladesh Cite this Article Md. Anwar Hossain, Zakir HM, Dipok Kumar et al. Quality and Metallic Pollution Level in Surface Waters of an Urban Industrialized City: A Case Study of Chittagong City, Bangladesh. Journal of Industrial Safety Engineering . 2017; 4(2): 9–18p.

Industrial safety engineering—Challenges of the future

Safety management is now entering an era quite different to that which marked its foundation. The multiple challenges facing safety engineering are focused upon. In the United States, France, Britain, and Brazil, safety engineering has experienced fast growth over the past two decades. An increased questioning of the traditional assumptions of the profession in both traditional and postindustrial work has accompanied this growth. New directions of reflection and research are being pursued. Recent research in sociology, where worker perceptions of tasks and their dangers are incorporated into the analysis of accident production, brings promising but still incipient new perspectives to accident research and theory. Simultaneously, novel challenges for safety engineering are posed by the emergence of postindustrial technologies. Some of these threaten large civilian populations, and the knowledge is not currently available to guarantee accident prevention. In this way the responsibilities of safety engineering, both ethical and with regards the provision of information to the public, are brought under the spotlight. The face of safety engineering is being changed.

Potential applications of fuzzy sets in industrial safety engineering

This paper discusses potential applications of fuzzy set theory to risk analysis in the area of industrial safety engineering. Vagueness and imprecision in mathematical quantification of risk are equated with fuzziness rather than randomness. The concept of risk evaluation, using linguistic representation of the likelihood of the occurrence of a hazardous event, exposure, and possible consequences of that event, is proposed. The approximate reasoning technique based on fuzzy logic is used to derive fuzzy values of risk.

Anatomy of an Accident

The findings of industrial safety engineers in the areas of accident causation and prevention are wholly applicable to adventure programs. Adventure education instructors can use safety engineering concepts to assess the risk in a particular activity, understand factors that cause accidents, and intervene to minimize injuries and damages if accidents occur. Language: en

Human Factors in Agricultural Tractor Safety

Agriculture is the third most hazardous industry, following mining and construction. Some reasons for this relate to the nature of agricultural machines and the conditions under which they are operated. Only 5% of all U.S. workers were engaged in agriculture in 1973, but these accounted for 17% of all work related injuries. Farm machinery was involved in the greatest number of these accidents. The economic cost of farm accidents is rising rapidly. Human factors engineering can be applied in the analysis of man/machine/environment/task relationships in agriculture. However, most conditions or assumptions applicable to industrial safety engineering do not apply in agricultural operations where variability, self-reliance, and self-management are the rule. This paper presents a survey of the current state of the art in applying human factors to agricultural tractors and explores some current research frontiers as well as some possibilities for future research.

The mechanism of isocyanate interaction with alcohols

Hazard and operability analysis (HAZOP) is a remarkable representative in industrial safety engineering. However, a great storehouse of industrial safety knowledge (ISK) in HAZOP reports has not been thoroughly exploited. In order to reuse and unlock the value of ISK and optimize HAZOP, we have developed a novel knowledge graph for industrial safety (ISKG) with HAZOP as the carrier through bridging data science and engineering design. Specifically, firstly, considering that the knowledge contained in HAZOP reports of different processes in industry is not the same, we creatively developed a general ISK standardization framework, it provides a practical scheme for integrating HAZOP reports from various processes and uniformly representing the ISK with diverse expressions. Secondly, we conceive a novel and reliable information extraction model based on deep learning combined with data science, it can effectively mine ISK from HAZOP reports, which alleviates the obstacle of ISK extraction caused by the particularity of HAZOP text. Finally, we build ISK triples and store them in the Neo4j graph database. We take indirect coal liquefaction process as a case study to develop ISKG, and its oriented applications can optimize HAZOP and mine the potential of ISK, which is of great significance to improve the security of the system and enhance prevention awareness for people. ISKG containing the ISK standardization framework and the information extraction model sets an example of the interaction between data science and engineering design, which can enlighten other researchers and extend the perspectives of industrial safety.

Safety at the Wheel

<h3>To the Editor:—</h3> I thankThe Journalfor the excellent editorial "Safety at the Wheel" (<i>JAMA</i><b>190</b>:391 [Oct 26] 1964). Some years ago, being impressed and depressed by the increasing death rate and injury rate of children from accidental injury, I got the idea that we need an elite corps of safety engineers for children. However, I found that the industrial safety engineers themselves seem to believe that the improvements in industry could not reasonably be attributed to their efforts, but rather to the realization on the part of management that accidental injuries are prohibitively costly. Our society seems to be reasonably well organized for the protection of industrial workers, but not for the protection of children. How can the costs of non-industrial accidents be made to work for prevention? Would it be better, as suggested by Dr. John M. Higginbotham of Birmingham, Ala, to have the chief liability