A step-by-step performance assessment and improvement method for ERP implementation: Action case studies in Chinese companies

The implementation of enterprise resource planning (ERP) is a complex process, and the failure rate remains very high. The literature has reported over 80 critical success factors for ERP implementation, but companies typically do not know to exploit them. In this article, a step-by-step assessment and improvement method for ERP implementation is proposed and applied in three companies. First, a five-stage ERP implementation model is proposed. Second, about 80 critical success factors (CSFs) from the literature are elaborated into key performance indices (KPIs), which are associated with each stage of ERP implementation by ten local ERP experts. Third, the weights of the KPIs are calculated using the Dumpster–Shafer method and the evaluation of ten experts. During the implementation process, performance is measured at each stage and remedial actions are identified if the performance is below expectation. An implementation flowchart is developed based on a five-stage model and the philosophy of continuous improvement. Three action cases in Chinese manufacturing companies are conducted to illustrate the effects of the assessment model, which is also currently being used by a consulting company specialising in ERP implementation. With further evaluation by local experts, the model has the potential to serve as a guideline for ERP implementation in other countries.     

A new multi criteria decision making approach for medical imaging systems considering risk factors

Effective and good quality imaging is important for medical decision-making and can reduce unnecessary costs and procedures. Therefore, decision making regarding any technology can present serious problems for healthcare centers with multi criteria decision making problems (MCDM). This paper is the first to develop the fuzzy axiomatic design with risk factors (RFAD) approach and to use it in multi attribute comparisons of medical imaging systems in a university hospital. Although most MCDM approaches in the literature treat risk factors as separate criteria, in real life every alternative has its own risks related to each criterion. The proposed approach integrates the risk factors in each criterion and calculates the information content to compare alternatives. This paper applies three different approaches to MCDM problems related to the selection of medical imaging systems for a university hospital.     

Ranking of aircraft maintenance organization based on human factor performance

Aircraft maintenance organisation is a complex socio-technical setup, where human factors influence the quality of aircraft maintenance service. Maintenance service quality is assessed based on the commitment of management and its ability to provide suitable facility, tools, spares and manpower supported with comfortable environment and maintenance procedures. Assessment of the service quality of the aircraft maintenance organisation is a complex process. Airlines, regulators, insurance companies and other agencies need decision support system, to assess the performance of a maintenance organisation. This paper provides criteria and scientific approach for assessing the maintenance organisation; it presents a methodology of applying Analytical Hierarchy Process to prioritise the key functions and to rank the maintenance organisations under study. The study has established that maintenance service quality in airline is directly correlated to its fleet size.     

Influence of the glassware on the perception of alcoholic drinks

Two studies are reported in which the effect of glassware was investigated on subjective ratings of, and willingness-to-pay for, alcoholic drinks. Participants from China (Study 1) and the USA (Study 2) viewed online photographs of red wine, white wine, beer, whisky, and Chinese baijiu presented in 6 different glasses, including a narrow, wide, or stemless wine glass, a highball or rocks glass, and a beer mug. They rated liking, familiarity, and congruency (between the drink and the glassware), as well as how much they would be willing to pay for the drinks. Both the type of drink and the type of glassware influenced participants’ subjective ratings of, and willingness-to-pay for, the drinks. The red and white wine were liked more, and people were willing to pay significantly more for if they thought that the glassware was congruent with the contents. These findings highlight the influence of content–context congruency on consumers’ subjective ratings and willingness-to-pay.     

里必井田承压水带压开采评估

煤层底板承压水突出是发生水害事故的原因之一,要减少该类事故的发生,需对底板突水危险性进行准确评价。为保障里必井田承压水带压开采的安全进行,基于煤层底板突水研究理论分析,采用常规突水系数法和等效厚度突水系数法,分别对里必井田内3#煤和15#煤的奥灰水突水危险性进行了研究。研究发现,奥灰水对于3#煤的开采影响不大,但在局部构造及陷落柱发育地段及采区东北部区域仍存在一定的突水可能性;奥灰水对15#煤开采具有较大威胁,大部分区域具有较大突水危险性。等效岩层厚度法计算的突水系数考虑了不同性质岩层的岩石强度和阻水能力,计算更接近生产实际,结果更可靠;且在对突水系数法进一步优化后,其评价的结果可以更精确。     

Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing

Although predictive machine learning for supply chain data analytics has recently been reported as a significant area of investigation due to the rising popularity of the AI paradigm in industry, there is a distinct lack of case studies that showcase its application from a practical point of view. In this paper, we discuss the application of data analytics in predicting first tier supply chain disruptions using historical data available to an Original Equipment Manufacturer (OEM). Our methodology includes three phases: First, an exploratory phase is conducted to select and engineer potential features that can act as useful predictors of disruptions. This is followed by the development of a performance metric in alignment with the specific goals of the case study to rate successful methods. Third, an experimental design is created to systematically analyse the success rate of different algorithms, algorithmic parameters, on the selected feature space. Our results indicate that adding engineered features in the data, namely agility, outperforms other experiments leading to the final algorithm that can predict late orders with 80% accuracy. An additional contribution is the novel application of machine learning in predicting supply disruptions. Through the discussion and the development of the case study we hope to shed light on the development and application of data analytics techniques in the analysis of supply chain data. We conclude by highlighting the importance of domain knowledge for successfully engineering features.     

Systematic tool to plan and evaluate demand side strategies during sustained energy crises in hydrothermal power systems

HARE, a systematic tool to evaluate demand side measures to face sustained energy supply risk in hydrothermal power systems is presented in this paper. The main focus of the paper is to help centralized planners to systematically discuss, select, and plan the measures that better respond to the variety of critical situations that can arise due to expected energy shortage, integrate them into the usual medium-term scheduling tool and consequently keep the associated overall costs as low as possible. A medium-term definition of the system state is proposed as a decision-making aid, as well as a set of general energy saving measures that can be applied with their corresponding attributes (time delays, costs of implementation, and energy saving impact). The tool is demonstrated and applied to a simplified version of Chilean’s medium-term hydrothermal scheduling model and to a specific risk scenario experienced during 2011. The results show that it is possible to define various sets of demand side measures that avoid the impacts on the system and subsequently to select among them those with least expected implementation costs. This tool seems mainly useful for hydro-electric systems, which are more vulnerable to sustained energy supply risk. Every power system will have to go through a detailed review and planning process to implement this type of tool.     

Data requirements for improving the Quantitative Risk Assessment of liquid hydrogen storage systems

Quantitative Risk Assessment (QRA) supports the development of risk-informed safety codes and standards which are employed to enable the safe deployment of hydrogen technologies essential to decarbonize the transportation sector. System reliability data is a necessary input for rigorous QRA. The lack of reliability data for bulk liquid hydrogen (LH₂) storage systems located on site at fueling stations limits the use of QRAs. In turn, this hinders the ability to develop the necessary safety codes and standards that enable worldwide deployment of these stations. Through a QRA-based analysis of a LH₂ storage system, this work focuses on identifying relevant scenario and probability data currently available and ascertaining future data collection requirements regarding risks specific to liquid hydrogen releases. The work developed consists of the analysis of a general bulk LH₂ storage system design located at a hydrogen fueling station. Failure Mode and Effect Analysis (FMEA) and traditional QRA modeling tools such as Event Sequence Diagrams (ESD) and Fault Tree Analysis (FTA) are employed to identify, rank, and model risk scenarios related to the release of LH₂. Based on this analysis, scenario and reliability data needs to add LH₂-related components to QRA are identified with the purpose of improving the future safety and risk assessment of these systems.     

城市排水管网风险评估研究

总结了常见的城市排水管网风险评估的方法及软件,对污水管网的气体爆炸风险、雨水管网的内涝风险、综合风险这三类风险评估的文献进行了归纳整理,并对未来的研究重点及趋势做出了预测。     

Occupational exposure and health risks of volatile organic compounds of hotel housekeepers: Field measurements of exposure and health risks

Hotel housekeepers represent a large, low-income, predominantly minority, and high-risk workforce. Little is known about their exposure to chemicals, including volatile organic compounds (VOCs). This study evaluates VOC exposures of housekeepers, sources and factors affecting VOC levels, and provides preliminary estimates of VOC-related health risks. We utilized indoor and personal sampling at two hotels, assessed ventilation, and characterized the VOC composition of cleaning agents. Personal sampling of hotel staff showed a total target VOC concentration of 57 ± 36 µg/m³ (mean ± SD), about twice that of indoor samples. VOCs of greatest health significance included chloroform and formaldehyde. Several workers had exposure to alkanes that could cause non-cancer effects. VOC levels were negatively correlated with estimated air change rates. The composition and concentrations of the tested products and air samples helped identify possible emission sources, which included building sources (for formaldehyde), disinfection by-products in the laundry room, and cleaning products. VOC levels and the derived health risks in this study were at the lower range found in the US buildings. The excess lifetime cancer risk (average of 4.1 × 10⁻⁵) still indicates a need to lower exposure by reducing or removing toxic constituents, especially formaldehyde, or by increasing ventilation rates.