Jan-2012

Cost estimating for turnarounds

Cost estimates for refinery turnarounds can lack accuracy, but lessons learned from capital project estimating could improve matters

Gordon Lawrence
Asset Performance Networks

Article Summary

Turnarounds are major events for refineries and other petrochemical facilities. They typically cost significant sums of operational expense (opex) and capital expense (capex) money to execute. They cause lost opportunity cost through lost production while the facility is shut down. If poorly managed, turnarounds offer significant risk of accidents. If poorly executed, they can also be the cause of significant production disruption after startup, due to leaks and other production trips. Hence, there is a potential to save significant sums of money, by ensuring turnarounds are run correctly.

However, despite the large potential for saving money, there has, until recently, been very little focus in the turnaround world on making sure turnarounds are run cost efficiently or on finding ways to improve cost estimating and execution skills. In the past seven to eight years, this attitude has begun to change and turnaround teams are beginning to look at how they can improve. One potentially rich source of ideas on how to improve is for the turnaround teams to examine how their capital project brethren estimate and execute projects. In the capital project world, the potential for “leaving money on the table” due to poor project estimating and execution has meant that decades of time and effort have been spent, and continue to be spent, on developing techniques to ensure that estimation and execution is carried out efficiently.

This article focuses on cost estimation. It does not presume to provide all the answers on how to improve turnaround cost estimates. Rather, it attempts to lay the groundwork for a discussion on how to improve cost estimating in process facility turnarounds. It highlights the point that cost estimating in the turnaround world is currently not very accurate. It then goes on to look at ideas on how to improve cost estimate accuracy, by looking at ideas that might be adapted from the capital project world. In particular, it looks at the stage gate approval system, the development of scope and estimate bases for different levels of estimate accuracy, and at the development of allowances for “known unknowns” and contingency for “unknown unknowns”. Finally, it makes some suggestions for the next steps in developing better turnaround cost estimates.

What is a process industry turnaround?
A turnaround (in the context of the process industries) is defined by the American Petroleum Institute as “a planned, periodic shutdown (total or partial) of a... process unit or plant to perform maintenance, overhaul and repair operations and to inspect, test and replace process materials and equipment”.1 Refineries and other petrochemical facilities that run on a continuous rather than a batch production cycle must, every few years, shut down operations to provide access to the production units in order that essential maintenance, modification and inspection work can be carried out that could not be done while the units are in operation.

Turnarounds are events that are planned well in advance and typically take place on a four-to-six year cycle. The length of a typical turnaround execution phase (ie, the period when the facility is shut down and hydrocarbon free) is usually around three-to-five weeks.

The scope of a turnaround typically includes:
• Inspection of equipment to company regulations or governmental rules
• Inspection of pipework for corrosion and erosion damage, both internal (process weak points) and external (corrosion under insulation, or CUI)
• Cleaning, repair and maintenance of equipment, pipework and instrumentation (pulling and cleaning heat exchanger tube bundles, repairing leaks in pipework or checking of pressure relief valves)
• Minor upgrades and modifications to the facilities (items controlled under the “management of change” [MoC] procedures)
• Tie-ins for capital projects.

Historically poor estimation and execution efficiency
Historically, there was a tendency among operating companies to view turnarounds as an inevitable and necessary evil, and to accept that they would “cost what they cost” and “take as long as they take”. However, in recent years, there has been a growing recognition that this attitude leaves “money on the table” in the form of the opportunity cost of lost production while the facility is shut down for longer than necessary; and unnecessarily excessive expenditure of money during the turnaround, through running the turnaround inefficiently.

In order to improve turnaround efficiency, there is a need to examine the estimation of costs for turnarounds, the estimation of schedule time, and the efficiency of planning and execution of the turnaround. This article focuses on the first of those three areas, the estimation of costs.

Accuracy of turnaround cost estimates
A cost estimate needs to be accurate in order to provide management with the information needed to decide how to proceed, to allow cash flow planning and to aid in firm control of expenditure.

In a survey of conference participants at the Turnaround Industry Networking Conference (TINC) —Europe, held in March 2011 in Amsterdam, The Netherlands,2 83% of respondents said that their turnaround control budget was intended to be a ±10% estimate (see Figure 1).3 The remaining 17% said that their estimate was supposed to include sufficient contingency/reserve that it was a “not to exceed” number. None said that their budget was intended to be a ±30% estimate.

We then took a sample of 93 recent turnarounds and in each case compared the total actual cost for the turnaround (including both capital and maintenance work) with the control budget. Figure 2 plots the over- or under-run of the actual costs, expressed as a percentage of the control budget. It shows the mean (the horizontal bar) and 80% confidence range (the vertical bar) of the results in our sample set and compares it to the results we would have expected if the cost estimates truly were ±10%, or if they were ±30%.