Risk Management in Engineering Projects - Report Example

RISK MANAGEMENT By Name Course Instructor Institution City/State Date Table of Contents RISK MANAGEMENT 1 Table of Contents 2 Risk Management 3 1.0 Analysis of the Articles 3 1.1 Introduction 3 1.2 Analysis of Methodologies and Data Collection 3 1.3 Interoperation Process 7 2.0 Research Project Proposal 10 2.1 Risk Management in Engineering Projects and Management Systems in Manufacturing Industry 10 2.2 Introduction 10 2.3 Background 11 2.4 Body of Report 11 2.5 Evaluation 13 2.6 Conclusion 14 3.0 References 15 Appendix 17 Risk Management 1.0 Analysis of the Articles 1.1 Introduction Scores of persons consider risk in engineering projects as a vague and unformulated issue that exists, and is difficult to manage. Whereas risk is undoubtedly ever-present, at times hard to perceive, and cannot at all times be totally circumvented, it may largely be reduced, mitigated, or stopped through well-timed action as well as analysis. Risk management may be described as a process of identifying and assessing risk, in addition to taking action so as to reduce it to a level that is acceptable. The approach for risk management governs the tools, techniques, processes, and team responsibilities and roles for certain engineering project. The plan and approach to risk management operationalize such management objectives. In this research paper, two articles Bristow et al. (2012) and Lee et al. (2013) will be analysed in terms of their methodology, data collection, and interoperation process. Subsequent to that, a project research will be proposed to further develop risk management in engineering projects and management systems. 1.2 Analysis of Methodologies and Data Collection According to Bristow et al. (2012) risk analysis must be scientifically rigorous as well as unbiased, but decisions made with regard to risk policies as well as assessments anchored in their outcomes are hardly without strategic, ideological, and political considerations. When a system of systems (SoS) experiences a risk attributed by an extreme event, risk assessment, communication, analysis as well as management may be so challenging for the reason that numerous participants are involved invariably. In Bristow et al. (2012) study, participants have been described as people who participate in a situation of risk whether individually or as a group generating a risk, whether unintentionally or intentionally, or endeavour to stop the risk situation, lessen its effects or counter the event. Participants as indicated in Bristow et al. (2012) study have dissimilar perceptions, attitudes, and values that may result in risk management disputes. Bristow et al methodological contribution is based on adaptive as well as integrative systems methodology in examining risks like strategic interactions amongst manifold participants. In this case, a practical use of the SoS engineering methodology is partly illustrated through a case study of a SoS interface in maritime infrastructure, specifically, transportation in the Straits of Straits of Malacca and Singapore. Data collection in the study was rooted in the case study. Bristow et al considered world-wide maritime transportation as a system for systems. Their case study concentrates mainly on the Straits of Singapore as well as Malacca, as an essential interface in the global sea transportation system of systems. Additionally, they case study concentrates on risk management with regard to extreme event wherein they consider the multiple participants strategic interactions instead of general global maritime SoS management. Bristow et al based their study on three expert workshops regarding governance of risk in global vital sea infrastructure concentrating on the Straits of Malacca and Singapore vulnerable to extreme hazards. The expert workshops were hosted by the Centre for Maritime Studies in April 2010, Disaster Prevention Research Institute at Kyoto University (DPRI-KU) in June 2009, as well as the International Risk Governance Council (IRGC) in November 2010. The above mentioned workshops offered the chance for interaction with participants from research institutions, industry, government, and international organizations, associated with maritime systems, as well as to get perspectives on the insights of the Straits of Singapore and Malacca as well as the insights of extreme events risk with regard to probabilities, consequences, and scenarios. Bristow et al based their argument on outcomes and details of the three workshops, which included numerous peer-reviewed. For purposes of explaining, Bristow et al designed an initial graph model for conflict resolution (GMCR) model for understanding the issue of ‘free-rider was built to act as a centre for debate amongst participants in the workshops. In this case, five participants who represented Indonesia, Malaysia, Singapore, and the private and the public user sector were considered by the model, For simplicity, all participants had the chance to make contribution to a common pool endowment for the modernisation as well as maintenance of navigational aids. In this case, contributing or not contributing to the fund was considered a decision for risk management decision. So, all participants had two probable strategies: to make contribution or not to. In this case, 25 = 32 is the total number of probable outcomes, considering that each of the five participants have one option. All outcomes were labelled from 1 to 32 and it represented participants’ strategies aggregation, where an “N” connoted that the participant was not willing to contribute while “Y” connoted participant willingness to contribute. For instance, as indicated in Bristow et al study outcome 16 is when Y is contributed by three participants (A, B, and C), but the two remaining participants do not contribute (N). Therefore, the problem of ‘free-rider’ surfaces because of the participant’s preferences; free riding according to Bristow et al connotes the verity that the Straits users can traverse them devoid of paying upgrading and maintenance cost of the infrastructure that enhances as well as keeps the security and safety of the Straits. According to Lee et al. (2013), manufacturing settings are unceasingly changing because of changes in technology as well as markets and due to the mounting concern concerning the environmental issues. These days’ businesses are facing aggressive competition as well as high expectations from customer, and so to remain economical and reduce costs of production, the value-added processes must be improved. The distributed manufacturing networks emergence has made engineering companies to realise the significance of controlling, monitoring and scheduling their processes across the globe. In this case, as mentioned by Lee et al. (2013) risks o system integration can take place if the processes are not monitored and controlled properly. So comprehending the transition as well as interaction of all processes is crucial and assists engineers in identifying and mitigating risks. The key purpose of Lee et al study is to explore both emerging as well as established risks that can crop up from distributed manufacturing system. And also to propose a methodology of risk analysis channelled through strong practices of risk management that may integrate Petri nets with risk analysis modelling so as to analyse risks disseminated in diverse processes of manufacturing. Besides that Lee et al designed a mathematical model appropriate for Monte Carlo simulation that had risk solver for risks analysis so as to lessen risks for activities related to distributed production. So they use a code-named company known as GG Manufacturing Pte Ltd as the case study and for data collection. According to Lee et al, GG Manufacturing Pte Ltd is a well-known industrial centre with well-resourced workshop facilities, and it upgrades and manufactures a range of machinery like turbines, nozzles, and buckets. Importantly, GG has a total quality management system that is certified of highly-experienced staffs to make certain that services and products exceed or meet quantified engineering requirements as well as quality standards. For the risk analysis in Lee et al study, one of GG product lines was chosen whereby the entire process flow was simplified. In this case, when goods are conveyed to system of production, the initial step is to carry out a quality check for the incoming. For the risks of information exchange risk, coordination risk as well as quality risk, Lee et al presumed that all of the risks had three levels: low, moderate, and high. So, in the risk solver 27 scenarios of risk were calculated by means of Monte Carlo simulation. The phases of employing the Monte Carlo simulation included: first, using a spread sheet to create a what-if analysis as well as design the simulation model. After that, the simulation model inputs are identified; based on various scenarios, the associated factors like quality cost as well as lead time are not the same. Such factors as mentioned by Lee et al have numerous uncertainty levels, so generally they are symbolised by values of distribution. In the methodology, there are more than 20 forms of distribution, like lognormal, normal, beta and the like. Lee et al methodology was rooted from past experts’ opinions as well as data, and insists that decision makers must choose the most suitable distribution patterns as well as simulation parameters. Third step involved setting the trials per simulation as well as carrying out simulations. Final phases entailed output data collection as well as performing statistical analysis for the outcome. 1.3 Interoperation Process As stated by Bristow et al. (2012, p.1942) resolution in risk context involves an outcome for risk management. The outcome entailed the strategies for risk management of every participant. In this case, the participant strategy involved options for risk management that the participants intended to take. An option for risk management as mentioned by Bristow et al is an action, which may be taken so as to prevent events from taking place, lessen severity or probability of an event, or counter the event. Various participants preferred some outcomes anchored on whether seeming risks reduced. It was noted that conflict crops up when one’s actions or that of other participants heighten costs or risks to others. As stated by Mathew et al. (2008, p.14), risk management must take into account the strategic interactions amongst partakers when conflict arises amongst participants, and it occurs when participants are many. The outcome of risk management is affected by strategic interactions, which, consequently, transforms the seeming level of risk for all participants. Through the knowledge of how different outcomes of risk management impact the perceived risks, the participants would enter into a game-like field wherein the game object was to attain a more favoured outcome from the current situation, for every participant. As mentioned by Bristow et al. (2012, p.1943), participants are adversaries in the sense that one participant action can heighten the costs and risks to the other. Strategies of risk management can be categorised as awareness, readiness as well as response, deterrence, and transfer. In Bristow et al. (2012, p.1947) case through traditional risk analysis, all participants were required to independently decide the severity of the risk, whether or not it was adequately high to warrant allocation of resources to manage the risk with the anticipation of decreasing the risk to anticipated level. Still, in a system of systems, interfaces may permit the unintentional increase of risk to others participants. For instance, individuals doing offences in Singaporean or Malaysian waters infrastructures can escape with no trouble into Indonesian waters. Risk management as mentioned in Lee et al. (2013) study with regard to distributed manufacturing is thought-provoking since the risks are disseminated in various distribution system units and is not easy to understand the transmission effect or aggregation of the risk. This has mainly been attributed by over-optimism and unawareness, as both engineers and company managers are more worried about productivity as well as profit than risk management. Still, poor management of risk as mentioned by Conrow (2003, p.67) may result in delay, high cost, and low throughput; so, it is imperative to achieve risk management effectiveness. Lee et al. (2013) echoes Bristow et al. (2012) by claiming that a distinctive risk management should involve risk identification, assessment, migration as well as monitoring. So, a skilled engineer should be able to identify risk sources and also be in a position to detect anomalous occurrences (Faulconbridge & Ryan, 2003, p.140). Factors of risks as mentioned by Ayyub (2014) can be different for various manufacturing companies depending on its size, structure, products, business values, as well as objectives. Risk focussed on a particular subsystem or module is somewhat easier to manage as comrade to those risks disseminated in diverse modules. Thus, it is imperative to understand and manage the process flow as well as inter-related activities within the system that may help engineers identify a possible risk. 2.0 Research Project Proposal 2.1 Risk Management in Engineering Projects and Management Systems in Manufacturing Industry 2.2 Introduction The manufacturing industry is facing unwanted as well as undesirable obstacles (operational disturbances) in its daily operations. Moreover, such disturbances as mentioned by Islam and Tedford (2012, p.258) put the industry at occupational, economic and production risks So as to manage such risks, the industry must implement a suitable process of risk management, and this is the key aim of proposing this research project. In the last two decades, manufacturing industry has generally concentrated heavily on innovative production and management activities so as to boost flexibility of manufacturing companies, improve quality of the products and also to boost innovative ability. Contrary, most of the manufacturing sectors (excluding the food and chemical sectors) concentrate less on risk management (Islam & Tedford, 2012, p.258). In this research, managing risks in engineering projects and management systems, particularly in manufacturing industry is proposed. 2.3 Background As stated by Bayer and Bustad (2012, p.9), the term risk may be explained and defined in many different ways relying on discussion perspective as well as aim. According to Hartford and Baecher (2004, p.92), a risk is an uncertainty integrated with a loss or damage, and further noted that not everything uncertain incur a risk. Still, in case an event is measured as both a loss and uncertain, then the risk can be described as a risk. Due to the scholarly disagreement that a risk is viewed in a different way relying on the objectives and experiences of the viewer, risk has turned out to be more and more crucial in manufacturing industry, especially in creating awareness as well as gaining information of possible risks (Bayer & Bustad, 2012, p.9). Besides that, because of the increasing number of terrorist attacks as well as natural disasters, in addition to manufacturing companies having highly internationalised supply chains, Handfield and McCormack (2007, p.51) posit that the number of risks that may have an effect on the supply chain of the organisation have heightened. This verity has created the necessity to concentrate on risk prevention as well as management. If a manufacturing lack knowledge concerning either the gains or losses of an engineering project, management systems or an investment, then estimating and managing risk becomes more harder leading to major losses for the company (Lam, 2003, p.208). 2.4 Body of Report Weak awareness about risk can result in negative consequence in the manufacturing companies, and this can be evidenced by Ericsson’s radio frequency chips’ single sourcing (Bayer & Bustad, 2012, p.9). In this case, New Mexico based Phillip’s plant was their only supplier of the chips, and when storms hit New Mexico in march 2000, it resulted to power failures leading to a fire that destroyed millions of chips (Chopra & Sodhi, 2004). As a consequence, Ericsson lost more than $400 million US dollars because of the lost days of production. This case proves that risk identification should be the initial step of the risk management process, and further reveals the importance of creating awareness of every possible risk a particular engineering activity or project can bring. Therefore, if Ericsson was aware of the possible risks brought about by outsourcing to a single supplier, they would have generated a plan of how to circumvent the event that took place in New Mexico or mitigate its effects. Even though manufacturing industry integrates techniques of project management in its operations (for investment as well as product development), Islam and Tedford (2012, p.258) posit that risk management is still seen as an anomaly. In risk management context, manufacturing companies concentrate largely on organization-led or government-led regulations for safety as well as health. The problem of relying just on methods of compliance verification for safety is that the company is not keenly creating ideal safety for its engineering project and management systems. Observance to the regulations and standards largely needs the minimum effort and mostly is not adequate to prevent industrial accidents. As stated by Islam and Tedford (2012, p.258), in manufacturing industry safety systems must be optimized by shifting the way engineers and managers think to continually make the system safer as well as not to unseeingly adhere to the regulations. Safety practices like occupational safety and health as well as other programs related to safety must, if appropriately executed and practiced, guarantee an improved working environment in the manufacturing companies. Still, they do not guarantee the smooth operation of the company or reduce its risks financially, technically and operationally. Inability of companies to handle their internal as well as external disturbances may lead to interruptions in engineering projects and also affect management systems, so risk management in manufacturing industry is exceedingly crucial. 2.5 Evaluation In Bristow et al. (2012) and Lee et al. (2013) they do not indicate how putting into practice a novel approach like risk management can help in managing commitment as well as knowledge. Since, the full commitment and suitable knowledge from engineers make certain successful of risk management. As defined by Mohamad et al. (2009, p.35), a risk management implementation structure is a flow of process, which is involved in all company’s business activities. Further, the two authors failed to mention the significance of creating awareness concerning risk management process to facilitate understanding amongst workers and enable them to offer full co-operation. Risk management process structure must be learned, and be comprehended before ensuring that it is part of the company culture. As mentioned by Lee et al. (2013, p.2665), businesses in distributed systems for manufacturing must have operational communication, co-ordination and collaboration with one another. Therefore, any disturbance in particular modules in the network of production may paralyse the distributed system. Scores of organisations cannot comprehend the system integration risks since they are often worried about their individual risks. Furthermore, the troubles of the organisation identifying and realising the possible risks at numerous areas can make the manufacturing company impassive until an unforeseen event happens. On the other hand, Bristw et al. (2012) proposes a system for systems engineering methodology to integratively create an amplified paradigm that takes into account both risk to the system by means of various frames as well as the strategic interactions amongst participants in process of risk management. However, the methodology calls for the participation of modellers, managers, experts, and decision makers to adaptively improve varied system paradigms as well as to interactively seek answers that result in looked-for risk management outcomes, which purposefully are stable. However, the two authors fail to explicitly talk about engineers’ role in risk management processes, and do not offer solutions that can be espoused by manifesting industry to improve their current state of risk management systems. 2.6 Conclusion For engineering projects, the risk management plan illustrates how risk management is designed and carried out. Risk management as a process of management is utilised for identifying and avoiding the possible schedule, cost, as well as technical/performance risks to an engineering system, take a structured and proactive approach to managing undesirable consequences, countering them in case the happen, and identify possible opportunities that may be concealed in such circumstances. There is need for more research on this field, as evidenced by insufficient literatures concerning the topic. 3.0 References Ayyub, B.M., 2014. Risk Analysis in Engineering and Economics. 2nd ed. New York: CRC Press. Bayer, E. & Bustad, G.Ö., 2012. Introducing Risk Management Process to a manufacturing industry. Master Thesis. Stockholm: Royal Institute of Technology. Bristow, M., Fang, L. & Hipel, K.W., 2012. System of Systems Engineering and Risk Management of Extreme Events: Concepts and Case Study. Risk Analysis, vol. 32, no. 11, pp.1935-54. Chopra, S. & Sodhi, M.S., 2004. Managing Risk to Avoid Supply-Chain Breakdown. [Online] Available at: http://sloanreview.mit.edu/article/managing-risk-to-avoid-supplychain-breakdown/ [Accessed 13 March 2015]. Conrow, E.H., 2003. Effective Risk Management: Some Keys to Success. New York: AIAA. Faulconbridge, R.I. & Ryan, M.J., 2003. Managing Complex Technical Projects: A Systems Engineering Approach. London: Artech House. Handfield, R. & McCormack, K.P., 2007. Supply Chain Risk Management: Minimizing Disruptions in Global Sourcing. New York: CRC Press. Hartford, D.N.D. & Baecher, G.B., 2004. Risk and Uncertainty in Dam Safety. Thomas Telford. Islam, D.M.A. & Tedford, D.D., 2012. Implementation of risk management in manufacturing industry- An empirical investigation. IRACST- International Journal of Research in Management & Technology, vol. 2, no. 3, pp.258-67. Lam, J., 2003. Enterprise Risk Management: From Incentives to Controls. New York: John Wiley & Sons. Lee, C.K.M., Lv, Y. & Hong, Z., 2013. Risk modelling and assessment for distributed manufacturing system. International Journal of Production Research, vol. 51, no. 9, pp.2652–66. Mathew, J., Ma, L., Tan, A. & Anderson, D., 2008. Engineering Asset Management: Proceedings of the First World Congress on Engineering Asset Management (WCEAM) 2006. New York: Springer Science & Business Media. Mohamad, E., Haslina, N., Saptari, A. & Salleh, M.R., 2009. The Implementation Of Risk Management At Aerospace Manufacturing Company. Journal of Human Capital Development, vol. 2, no. 1, pp.25-36. Appendix ME7711- Engineering Research Techniques Project Proposal Template Proposer Name: Id Number: Project Title: Risk Management in Engineering Projects and Management Systems in Manufacturing Industry Introduction and Project Background Research: The manufacturing industry is facing unwanted as well as undesirable obstacles (operational disturbances) in its daily operations. Inability of companies to handle their internal as well as external disturbances may lead to interruptions in engineering projects and also affect management systems. The number of risk that may have an effect on the supply chain of the organisation have heightened. This verity has created the necessity to concentrate on risk prevention as well as management. Project Aim and Objectives: 1. To examine the nature of risk management and develop a structure of risk management 2. Process 3. To identify and map the internal risks in the manufacturing industry 4. To measure the effectiveness of the implanting risk management process in manufacturing companies 5. To examine the risk management principles as well as supporting tools currently used in the manufacturing industry 6. To present a comprehensive framework for successful implementation of risk management in the manufacturing industry Intellectual Challenge: I was intellectually challenged by this topic, since intellectual process of using skilful reasoning was plagued with lack of adequate literature on risk management in engineering projects. Moreover, the concept of a knowledge gap between engineers as practitioners and academics was exceedingly challenging. Methodology and Plan: The study will use numerous means and approaches of collecting data, which will range from case studies, surveys, and review of literatures, with the intention of ensuring that the study objectives and aims are realised. In this case, the study will pursue a qualitative research method, mainly survey so as to get perceptions as well as opinions concerning risk management in engineering projects and management systems in manufacturing industry. Project Deliverables: Predesign (estimating, feasibility study, technology evaluation, and conceptual design); design (detailed and front end engineering, cost control, system integration, safety planning); start up (system checkout and engineering support); replacing obsolete systems. Resources Required: Mobile devices (laptop and mobile phones), Transport, software for data analysis and simulation, impetrator, and mailing services (for sending questionnaires). Bibliography/References 1. Bayer, E. & Bustad, G.Ö., 2012. Introducing Risk Management Process to a manufacturing industry. Master Thesis. Stockholm: Royal Institute of Technology. 2. Bristow, M., Fang, L. & Hipel, K.W., 2012. System of Systems Engineering and Risk Management of Extreme Events: Concepts and Case Study. Risk Analysis, vol. 32, no. 11, pp.1935-54. 3. Chopra, S. & Sodhi, M.S., 2004. Managing Risk to Avoid Supply-Chain Breakdown. [Online] Available at: http://sloanreview.mit.edu/article/managing-risk-to-avoid-supplychain-breakdown/ [Accessed 13 March 2015]. 4. Handfield, R. & McCormack, K.P., 2007. Supply Chain Risk Management: Minimizing Disruptions in Global Sourcing. New York: CRC Press. 5. Hartford, D.N.D. & Baecher, G.B., 2004. Risk and Uncertainty in Dam Safety. Thomas Telford. 6. Islam, D.M.A. & Tedford, D.D., 2012. Implementation of risk management in manufacturing industry- An empirical investigation. IRACST- International Journal of Research in Management & Technology, vol. 2, no. 3, pp.258-67. 7. Lam, J., 2003. Enterprise Risk Management: From Incentives to Controls. New York: John Wiley & Sons. 8. Lee, C.K.M., Lv, Y. & Hong, Z., 2013. Risk modelling and assessment for distributed manufacturing system. International Journal of Production Research, vol. 51, no. 9, pp.2652–66. 9. Mohamad, E., Haslina, N., Saptari, A. & Salleh, M.R., 2009. The Implementation Of Risk Management At Aerospace Manufacturing Company. Journal of Human Capital Development, vol. 2, no. 1, pp.25-36. Read More