Generic and configurable diagnosis function based on production data stored in Manufacturing Execution System

International audienceThe paper proposes a diagnosis approach corresponding to the specific MES level to provide information on the origins of a performance indicator degradation. Our key distribution is the proposal of a set of potential causes that may impact the successful completion of production operations, such as the operator stress, quality of material, equipment or recipe change and their characteristic parameters by exploiting MES historical database. We use Bayesian Network model to diagnose the potential failure causes and support effective human decisions on corrective actions (maintenance, human resource planning, recipe re-qualification, etc) by computing conditional probabilities for each suspected proposed causes

Operational risk management in high-mix, low-volume production

Abstract. The objective of this Master’s thesis is to study operational risk management in High-Mix, Low-Volume production, with a focus on small and medium-sized enterprises. This objective is achieved through answering three research questions regarding previous literature, current state in a case company, and improving practises in the case company. This thesis is conducted as a qualitative research utilizing a literature review and a single case study. The literature review is utilized to form the theoretical foundation for the thesis, and to answer the first research question, providing the state of previous literature. The case study is utilized to obtain the current state in the case company, which answers the second research question. Case study data includes documentary data, observations, and interviews. Three semi-structured interviews were conducted, and the observations were obtained with participatory observing. The third research question is answered by comparing the empirical study and literature to provide improvement recommendations to the case company. The findings of this study include the empirical results of operational risk management in a single case example, as well as the proposed improvements for the case company. The empirical observations are described in detail, and guidance for future studies is given. The development proposals are directly applicable to the case company and are expected to result in a higher operational risk management capability. The literature review and empirical observations may be useful to other researchers or organizations, but the recommendations have limited generalizability outside the case company. However, some of the recommendations might be applicable to a company with similar practises or organizational context.Operatiivisten riskien hallinta korkean vaihtuvuuden ja matalan volyymin tuotantoympäristöissä. Tiivistelmä. Tämän diplomityön tavoitteena on tutkia operatiivisten riskien hallintaa korkean vaihtuvuuden ja matalan volyymin (High-Mix, Low-Volume) tuotantoympäristöissä, pienissä ja keskisuurissa yrityksissä. Työn tavoite saavutetaan vastaamalla kolmeen tutkimuskysymykseen liittyen aiempaan kirjallisuuteen, case-yrityksen nykytilaan ja case-yrityksen toiminnan parantamiseen. Diplomityö toteutetaan laadullisena tutkimuksena, jossa hyödynnetään kirjallisuuskatsausta ja case-tutkimusta. Kirjallisuuskatsaus muodostaa tutkimuksen teoreettisen viitekehyksen ja vastaa ensimmäiseen tutkimuskysymykseen esittelemällä aiempaa tutkimusta. Case-tutkimusta hyödynnetään case-yrityksen nykytilan kuvaamiseen, mikä antaa vastauksen toiseen tutkimuskysymykseen. Case-tutkimuksen aineisto koostuu case-yrityksen riskienhallintaan liittyvistä dokumenteista, havainnoista ja haastatteluista. Tutkimuksen osana suoritettiin kolme puolistrukturoitua haastattelua ja havainnot kerättiin osallistuvalla havainnoinnilla. Kolmanteen tutkimuskysymykseen vastataan empiirisen tutkimuksen ja kirjallisuuden vertailulla, jonka tuloksena saadaan ehdotuksia case-yrityksen toiminnan parantamiseen. Tutkimuksen tuloksia ovat empiiriset havainnot yksittäisestä case-yrityksestä sekä parannusehdotukset case-yrityksen operatiivisten riskien hallintaan. Tarkkaan kuvattujen empiiristen havaintojen lisäksi työssä ohjeistetaan aiheeseen liittyvää jatkotutkimusta. Annetut parannusehdotukset ovat suoraan sovellettavissa case-yritykseen ja niiden odotetaan johtavan korkeampaan operatiivisten riskien hallinnan kyvykkyyteen. Toiset organisaatiot ja tutkimukset voivat hyötyä kirjallisuuskatsauksesta ja empiirisistä havainnoista, mutta parannusehdotuksilla on rajallinen yleistettävyys case-yrityksen ulkopuolelle. Jotkin parannusehdotukset voivat kuitenkin olla sovellettavissa yrityksiin, joilla on samankaltaisia käytänteitä tai piirteitä

Uncertainty analysis in product service system: Bayesian network modelling for availability contract

There is an emerging trend of manufacturing companies offering combined products and services to customers as integrated solutions. Availability contracts are an apt instance of such offerings, where product use is guaranteed to customer and is enforced by incentive-penalty schemes. Uncertainties in such an industry setting, where all stakeholders are striving to achieve their respective performance goals and at the same time collaborating intensively, is increased. Understanding through-life uncertainties and their impact on cost is critical to ensure sustainability and profitability of the industries offering such solutions. In an effort to address this challenge, the aim of this research study is to provide an approach for the analysis of uncertainties in Product Service System (PSS) delivered in business-to-business application by specifying a procedure to identify, characterise and model uncertainties with an emphasis to provide decision support and prioritisation of key uncertainties affecting the performance outcomes. The thesis presents a literature review in research areas which are at the interface of topics such as uncertainty, PSS and availability contracts. From this seven requirements that are vital to enhance the understanding and quantification of uncertainties in Product Service System are drawn. These requirements are synthesised into a conceptual uncertainty framework. The framework prescribes four elements, which include identifying a set of uncertainties, discerning the relationships between uncertainties, tools and techniques to treat uncertainties and finally, results that could ease uncertainty management and analysis efforts. The conceptual uncertainty framework was applied to an industry case study in availability contracts, where each of the four elements was realised. This application phase of the research included the identification of uncertainties in PSS, development of a multi-layer uncertainty classification, deriving the structure of Bayesian Network and finally, evaluation and validation of the Bayesian Network. The findings suggest that understanding uncertainties from a system perspective is essential to capture the network aspect of PSS. This network comprises of several stakeholders, where there is increased flux of information and material flows and this could be effectively represented using Bayesian Networks

ISBIS 2016: Meeting on Statistics in Business and Industry

This Book includes the abstracts of the talks presented at the 2016 International Symposium on Business and Industrial Statistics, held at Barcelona, June 8-10, 2016, hosted at the Universitat Politècnica de Catalunya - Barcelona TECH, by the Department of Statistics and Operations Research. The location of the meeting was at ETSEIB Building (Escola Tecnica Superior d'Enginyeria Industrial) at Avda Diagonal 647. The meeting organizers celebrated the continued success of ISBIS and ENBIS society, and the meeting draw together the international community of statisticians, both academics and industry professionals, who share the goal of making statistics the foundation for decision making in business and related applications. The Scientific Program Committee was constituted by: David Banks, Duke University Amílcar Oliveira, DCeT - Universidade Aberta and CEAUL Teresa A. Oliveira, DCeT - Universidade Aberta and CEAUL Nalini Ravishankar, University of Connecticut Xavier Tort Martorell, Universitat Politécnica de Catalunya, Barcelona TECH Martina Vandebroek, KU Leuven Vincenzo Esposito Vinzi, ESSEC Business Schoo

Improving water asset management when data are sparse

Ensuring the high of assets in water utilities is critically important and requires continuous improvement. This is due to the need to minimise risk of harm to human health and the environment from contaminated drinking water. Continuous improvement and innovation in water asset management are therefore, necessary and are driven by (i) increased regulatory requirements on serviceability; (ii) high maintenance costs, (iii) higher customer expectations, and (iv) enhanced environmental and health/safety requirements. High quality data on asset failures, maintenance, and operations are key requirements for developing reliability models. However, a literature search revealed that, in practice, there is sometimes limited data in water utilities - particularly for over-ground assets. Perhaps surprisingly, there is often a mismatch between the ambitions of sophisticated reliability tools and the availability of asset data water utilities are able to draw upon to implement them in practice. This research provides models to support decision-making in water utility asset management when there is limited data. Three approaches for assessing asset condition, maintenance effectiveness and selecting maintenance regimes for specific asset groups were developed. Expert elicitation was used to test and apply the developed decision-support tools. A major regional water utility in England was used as a case study to investigate and test the developed approaches. The new approach achieved improved precision in asset condition assessment (Figure 3–3a) - supporting the requirements of the UK Capital Maintenance Planning Common Framework. Critically, the thesis demonstrated that, on occasion, assets were sometimes misallocated by more than 50% between condition grades when using current approaches. Expert opinions were also sought for assessing maintenance effectiveness, and a new approach was tested with over-ground assets. The new approach’s value was demonstrated by the capability to account for finer measurements (as low as 10%) of maintenance effectiveness (Table 4-4). An asset maintenance regime selection approach was developed to support decision-making when data are sparse. The value of the approach is its versatility in selecting different regimes for different asset groups, and specifically accounting for the assets unique performance variables

Modelo de apoio à decisão para a manutenção condicionada de equipamentos produtivos

Doctoral Thesis for PhD degree in Industrial and Systems EngineeringIntroduction: This thesis describes a methodology to combine Bayesian control chart and CBM (Condition-Based Maintenance) for developing a new integrated model. In maintenance management, it is a challenging task for decision-maker to conduct an appropriate and accurate decision. Proper and well-performed CBM models are beneficial for maintenance decision making. The integration of Bayesian control chart and CBM is considered as an intelligent model and a suitable strategy for forecasting items failures as well as allow providing an effectiveness maintenance cost. CBM models provides lower inventory costs for spare parts, reduces unplanned outage, and minimize the risk of catastrophic failure, avoiding high penalties associated with losses of production or delays, increasing availability. However, CBM models need new aspects and the integration of new type of information in maintenance modeling that can improve the results. Objective: The thesis aims to develop a new methodology based on Bayesian control chart for predicting failures of item incorporating simultaneously two types of data: key quality control measurement and equipment condition parameters. In other words, the project research questions are directed to give the lower maintenance costs for real process control. Method: The mathematical approach carried out in this study for developing an optimal Condition Based Maintenance policy included the Weibull analysis for verifying the Markov property, Delay time concept used for deterioration modeling and PSO and Monte Carlo simulation. These models are used for finding the upper control limit and the interval monitoring that minimizes the (maintenance) cost function. Result: The main contribution of this thesis is that the proposed model performs better than previous models in which the hypothesis of using simultaneously data about condition equipment parameters and quality control measurements improve the effectiveness of integrated model Bayesian control chart for Condition Based Maintenance.Introdução: Esta tese descreve uma metodologia para combinar Bayesian control chart e CBM (Condition- Based Maintenance) para desenvolver um novo modelo integrado. Na gestão da manutenção, é importante que o decisor possa tomar decisões apropriadas e corretas. Modelos CBM bem concebidos serão muito benéficos nas tomadas de decisão sobre manutenção. A integração dos gráficos de controlo Bayesian e CBM é considerada um modelo inteligente e uma estratégica adequada para prever as falhas de componentes bem como produzir um controlo de custos de manutenção. Os modelos CBM conseguem definir custos de inventário mais baixos para as partes de substituição, reduzem interrupções não planeadas e minimizam o risco de falhas catastróficas, evitando elevadas penalizações associadas a perdas de produção ou atrasos, aumentando a disponibilidade. Contudo, os modelos CBM precisam de alterações e a integração de novos tipos de informação na modelação de manutenção que permitam melhorar os resultados.Objetivos: Esta tese pretende desenvolver uma nova metodologia baseada Bayesian control chart para prever as falhas de partes, incorporando dois tipos de dados: medições-chave de controlo de qualidade e parâmetros de condição do equipamento. Por outras palavras, as questões de investigação são direcionadas para diminuir custos de manutenção no processo de controlo.Métodos: Os modelos matemáticos implementados neste estudo para desenvolver uma política ótima de CBM incluíram a análise de Weibull para verificação da propriedade de Markov, conceito de atraso de tempo para a modelação da deterioração, PSO e simulação de Monte Carlo. Estes modelos são usados para encontrar o limite superior de controlo e o intervalo de monotorização para minimizar a função de custos de manutenção.Resultados: A principal contribuição desta tese é que o modelo proposto melhora os resultados dos modelos anteriores, baseando-se na hipótese de que, usando simultaneamente dados dos parâmetros dos equipamentos e medições de controlo de qualidade. Assim obtém-se uma melhoria a eficácia do modelo integrado de Bayesian control chart para a manutenção condicionada

Strategic risk management in water utilities: development of a holistic approach linking risks and futures

Risk management plays a key role in water utilities. Although tools are well established at operational and tactical levels of management, existing methods at strategic level lack a holistic treatment and a long-term perspective. In fact, risks are analysed per se, despite being interconnected; and long-term scenarios are commonly used for strategic planning, rather than for risk management, most of the time being related to one single issue (for example: climate change). In order to overcome the limitations identified in the existing methodologies, a novel approach for water utilities to manage risk at strategic level was developed and tested in EPAL - the largest and oldest water utility in Portugal. It consists of (i) setting a baseline risks comparison founded on a systemic model developed ‗bottom-up‘ through the business; (ii) the construction of future scenarios and an observation of how baseline risks may change with time. Major contributions of this research are the linkage between operational and strategic risks, capturing the interdependencies between strategic risks; the ability to look at long term risk, allowing the visualizing of the way strategic risks may change under a possible future scenario; and the novel coupling of risks and futures research. For the water sector, this approach constitutes a useful tool for strategic planning, which may be presented to the Board of Directors in a simple and intuitive way, despite the solid foundations of the underlying analysis. It also builds on in-house expertise, promoting the dissemination and pervasiveness of risk management within the companies and, on the other hand, allowing unveiling of existing knowledge, making it explicit and more useful for the organization