Risk-based Maintenance Framework



Dairy Industry Crisis: Technical Solutions

 The European dairy industry is suffering a deep crisis during the last months due to the low prices of sales, under the production costs.

 According to the European Commission, the crisis has been driven by Russia's trade ban on Community food industry, added a demanding fall of milky products in China P.R. and other BRICS countries to a lesser extent, and a slight increase of the world production especially emphasizing Australia (2.5 %), USA (1.6 %), New Zealand, world's largest producer, (0.9 %) y the European Union (0.8 %).

 Summarizing, there has been a temporary drop in demand that joined a slight increase in production.

 The practical impact is the milk price is between 15 % and 35 % (depends on the EU area) under a price to give profitability enough to the producers.

What solutions can be applied?

 Both, the dairy producer associations and European Union governments propose the following measures:

• Setting minimum retail prices.
• Re-introduction of production quotas.
• Financial grant, to compensate for the drop in profitability. 
• Encourage innovation and develop new dairy products, to consume milk production.
• Creation of new cooperatives and associations, to apply economy of scale.

 Innovation and development of new dairy products are an excellent solution, it must be carried out at all times, but due to its high risk, high cost and high period of phasing, it doesn´t look the best short-term solution.

 Creation of cooperatives and associations will reduce costs and increase efficiencies, but supposes a short-time staff reduction by duplicities elimination.

 Regarding setting prices, re-introduction of quotas and financial grants, they don't suppose an improvement of producer's productivity, so the producers will be grants dependant and will lose market share.

An engineering solution.

 We can define productivity as a ratio of outputs (milk production) and inputs (resources needed for the production).

Productivity = Actual Outputs / Actual Inputs

 Let's analyze each term.

Actual Outputs: It's the result to multiplying production Capacity, Availability of the process (ratio of gross operating time and available production time), Performance of the process (ratio of net operating time and gross operating time), and Quality of the process (ratio of valuable operating time and net operating time).

In accordance with Lean Manufacturing methodology, the result of multiplying Availability, Performance, and Quality is defined as Overall Equipment Effectiveness (OEE):

Actual Outputs = Capacity * OEE

Actual Inputs: It's the result of the addition of human resources and physical resources; physical resources are the addition of Acquisition Costs, Operation Costs, Maintenance Costs, and Disposal Costs.

Resources = Human Resources + Acquisition Costs + Operation Costs + Maintenance Costs + Disposal Costs

 Therefore, to improve productivity is possible by the OEE increase, Acquisition, Operation, Maintenance and Disposal Costs; without increase the Capacity or reduce Labor Force Costs.

 To implant Lean policies, as Value Stream Mapping and pull system to eliminate wastes, to increase availability by Kanban and reduce human errors by Poka-Yoke allow increasing dramatically the real production without big capital investments.

 On the other hand, to implant a Physical Asset Management plan allows the physical resources optimization by implanting specific measures as Reliability Assurance programs and Reliability Centered Maintenance (RCM), taking into consideration the implantation risk.

 A sustainable solution.

 The implantation of both Lean and Physical Asset Management results in a quick rise of productivity, without the need for a large investment, without reducing the labor force, and controlling the risk associated.

 It provides a sustainable solution because it is focused on reducing costs; consequently, it increases competitiveness, at the same time increases production, and allows to rise of the market share and business profitability, releasing resources that may dedicate themselves to research, development, and innovation.

Trainings in Madrid / Cursos en Madrid

 En estos meses voy a impartir los siguientes cursos en Madrid. / Next months I'm going to give the following trainings and workshops in Madrid:

- Jornada sobre Gestión de un Sistema de Mantenimiento Eficaz, con Ángel Partida, en el COITIM el 6 de mayo. / Conference about Management of an Effectiveness Maintenance System, in collaboration with Ángel Partida, in COITIM, May 6th.


- Curso sobre Mantenimiento Lean y TPM, en Preditec 20 al 22 de mayo. / Course about Lean Maintenance and TPM, in Predictec May 20th to 22th.

- Curso sobre Gestión de Activos basada en Riesgos, en Preditec 17 al 19 de junio. / Course about Risk based Asset Management, in Predictec June 17th to 19th.


- Curso sobre Ingeniería de Fiabilidad y RCM, en Preditec 25 al 27 de junio. / Course about Reliability Engineering and RCM, in Predictec June 25th to 27th.


 Los cursos en Preditec son totalmente prácticos, utilizando la metodología de manos a la obra para que los asistentes puedan aprender el contenido de una forma sencilla y entretenida. / The courses in Preditec are full practical and use the hand-on methodology to ensure the attendants learn the topics in a easy and funny way.

Risk Based Maintenance: The latest maintenance strategy

 We can consider Risk-Based Maintenance (RBM) as an evolution of RCM (Reliability-Centered Maintenance), RCM is based in the equipment condition and the importance of equipment to system, but it is limited because it doesn’t solve the quantification of failures. (1)

 Due to this ability to quantify problems join its simplicity to implant, RBM has been successfully applied in Oil & Gas, petrochemical plants, power generation y distribution networks, etc... And it achieves important savings.

 API RP 580 Standard defines risk as to the combination of the probability of an event occurring during a time period and the consequences associated with the event. In mathematical terms:

                                       Risk = Probability X Consequence

 We can obtain and economic value (if the consequence is valued) or classification by a risk matrix.

 API considers the Risk-Based Inspections (RBI) as the next generation of inspection interval settings, focuses attention specifically on the equipment and associated deterioration mechanisms representing the most risk to the facility. It recognizes the ultimate goal of the inspection is the safety and reliability of facilities. (2)

 F.I. Khan and M.M. Haddara propose an RBM methodology (3) that is broken down into three modules:

•  Module I: Risk estimation, including a failure scenario development, a consequence assessment and a probability failure analysis, it can be conducted using Fault Tree Analysis (FTA).

• Module II: Risk Evaluation, setting up acceptance criteria and applying these criteria to the estimated risk for each unit in the system.

• Module III: Maintenance planning, optimizing the maintenance plan to reduce the probability of failure, reducing the total risk level of the system.

 In this module, we can use the measures to control and mitigate risks proposed in the ISO 17776 Standard, as prevention, la detection, and control. (4)

 Norsok Standard Z-008 (5) not only does RBM propose to design and update maintenance programs but proposes it to prioritizing maintenance activities and evaluates spare parts quantity and location.

 We find in RBM a more simple methodology than RCM, it also requires an initial reliability study but include an economic risk assessment, so it allows doing financial analysis and makes easier to choose timed based and on-condition tasks as well as complex actions as spare parts quantity and location, re-design of equipment or changes in the process.

  

(1)  Zhao M-X., Su J., Liu S-G. Risk assessment based maintenance management for distribution network. Journal of international council on electrical engineering Vol.2, No 1, pp. 84-89, 2012.

(2)  Risk-based Inspection. API Recommended Practice 580. 1st Edition, May 2002.

(3)  Khan F.I., Haddara M.M. Risk-based maintenance (RBM): A quantitative approach for maintenance/inspection scheduling and planning. Journal of loss prevention in the process industries 16 (2003) 561-573.

(4)  ISO 17776:2000 Petroleum and natural gas industries- Offshore production installations - Guidelines on tools and techniques for hazard identification and risk assessment. 1st Edition 2000-10-15.

(5)  Norsok Standard Z-008 Edition 3, June 2011. Risk based maintenance and consequence classification.