Asset Management in the Automated Terminal

Transcription

1 Asset Management in the Automated Terminal Michael Panosh GM International, Mainpac

2 Asset Management in the Automated Terminal Integration and automation are imperatives to manage cost, maximize throughput and enhance safety. Effectively delivering these outcomes requires a well-planned asset management strategy and this session discusses common issues and lessons learned to achieve the objective.

3 Our Credentials More than 25 years delivering Asset Management Software it is all we do! More than a decade of ports and terminal industry experience Customers across all terminal types Container, Bulk, Tank Storage, RoRo, Passenger etc. Headquartered in Sydney, Australia

4 The Asset Management Objective 1. Map your required standard of service to the assets you have; 2. Provide that standard of service in an optimal way*; and 3. Comply with, and support audit of, any regulatory, legislative or corporate frameworks that apply to your business. * This usually means at least cost and is most contentious issue in Asset Management across terminals today

5 Common Issue #1 For many terminals, Asset Management really means Keep the equipment running And Do it with 5% less budget than last year

6 In this context Engineering has a simple mandate: - Maintain your Equipment - Repair your Equipment - Overhaul your Equipment And when it eventually fails: - Replace your Equipment

7 Common Issue #2 Data Quality means different things to different people Details of a Work Order from one of our US customers - Clear to the Engineering team - Perhaps not so clear to other teams - But opaque to quantitative analysis tools

8 Without discipline data grows wild A recent review of a European customer found, in just one asset metric: 34 different asset classification values: - 9 of which are unused - The Straddle Carrier group has 734 pieces of equipment assigned - 4 groups with only one piece of equipment assigned Such inconsistency is typical but it makes meaningful analysis very difficult

9 Common Issue #3 Measurement is key to Asset Management, but: 1. It has to be repeatable 2. It has to be accurate 3. It has to be timely These are challenges in many terminals due to staff turnover, minimal automation and poor disciplines

10 KPIs are hard to get right Here is a KPI from one of our customers: KWh/QC/Month It is a reasonable metric, but this customer has no methodology to accurately and consistently measure KWh from their cranes. So they configured their system without any KWh meters against the QC asset hierarchy, meaning that they have to manually manipulate their KPI each month. Unfortunately, KPIs are often undelivered, whether useful or not

11 Automation Changes the Game

12 Because automation readily supports Those measures that are key to Asset Management 1. Repeatable access to asset details 2. Accurate access to asset details 3. Timely access to asset details

13 Of course, automation brings its own issues Automation can get complicated 1. Each application needs to be connected 2. There is a lot of data to handle 3. Connections can be: a) One-way (usually alerts and alarms) b) Two-way (the most common kind) c) Pass-through (one application mediates for another) Remember, the more connections, the harder it is to identify problems

14 A typical Asset Management automation expectation Terminal Operating System Planned Maintenance Availability/Handover Machine Running Hours Breakdown Reports Moves Capital Works Planning Approved Budget Reqs/POs Issues/Receipts Chart of Accounts Vendors Finance System Labor Management Crane Monitoring Planned Leave Labor Rates Sign In/Out Meter Readings Performance Data Moves Alarms Enterprise Asset Management System Consumption Issues Alarms Meter Readings Performance Data Fuel and Lubrication Building Management Access Control System Authorization Status Assigned Operators Current Position Equipment Location Services Tire Wear Shock Readings Service Request Speed Reading Meters General Alarms Fleet Management

15 Planning for Asset Management automation The following can help reduce cost and complexity when executing an automation project: 1. An Enterprise Services Bus (ESB) 2. Existing applications 3. Definition of Master Data sources 4. Distinct transaction/process flows 5. Clear KPIs and business metrics

16 Enterprise Services Bus (ESB) This is like the telephone/language translation exchange for your business applications to talk to each other and is useful where: You are integrating three or more applications/services You will plug-in more applications in the future Your applications use different communications protocols You will require sophisticated message routing You will publish services for consumption by other applications

17 Existing applications It sounds unlikely, but terminals are issuing tenders asking vendors to cost automation against applications that they have not even purchased yet: 1. The vendor should be charging you for this uncertainty (and if they are not, be worried) 2. Are you splitting your focus across too many projects to the detriment of all 3. What is the real problem that needs to be solved right now

18 Definition of Master Data sources Some data rightfully belongs in specific applications so they should be the Master Data source, such as: EAMS Fixed Asset Register, Meter Reads, Inventory, Requisitions, POs, Inventory Issues Finance System Chart of Accounts, Vendors, Accounts Payable, Accounts Receivable Labor Management System Staff ID, Labor Rates, Employment Contracts Capital Works System Project Budget, WIP Costs, Project Contracts

19 Distinct transaction/process flows Automation usually uncovers different viewpoints within the business which leads to fuzzy requirements: 1. Which Department rightfully owns this transaction 2. Do you have the level of detail down to the database field level 3. What business logic needs to be triggered when transactions arrive 4. Do you need to manipulate the transaction format upon exit/entry to the application

20 Automation = Detail There are 10 transaction types in this simple looking interface and each of these transaction types requires a distinct Web Service

21 And more detail Each Web Service requires a fully formed data model this is the GL Account Code structure (and it s the most straightforward of the lot) Account Code Format Account Type Division Department Category Account XXXXXX Ledger 1st character Characters 2-3 Characters 4-6 7XXXXX*XXXX Project 1st character Characters 2-3 Characters 4-6 All Characters after the '*' 5XXXXX-XXXX-XX Project '2', if the last 3 characters are '-01' '69' if the last 3 characters are '-01' Characters 4-6 All Characters after the first '-' '7' if the last character is 2 '99' otherwise 8XXXXX Customer 7 99 All characters except the first

22 And even more detail Many transactions will require field level transformation with content dependent logic this is an example of just one Field from the Creditor record Account IF Account Code is not provided THEN 'No A/C' ELSE IF Account Type = 'Customer THEN All but the first character of the Account Code ELSE IF Account Code contains a '/' or Account Code contains a '+ THEN The 3 characters of the Account Code before the '/' or the '+' character Replace any of the following characters with a space, before export:, * / - +. Warn if no Account code LL: Do not allow creation without an Account code. The screen manager can be used to make the Account code mandatory, for all order lines. ELSE IF Account Type = 'Project THEN The Account Code, from the 8th character onward ELSE Characters 4-6 of the Account Code

23 Clear KPIs and business metrics Automation can automate KPI generation, but deciding on KPIs is another common point of contention Does everyone agree that the metrics are relevant Is there a clear link between the metric and strategy Will the data need massaging before we can issue it If your objectives are unclear, automation won t help

24 But what if we get automation right? Then we can do meaningful analysis on assets such as root cause of failure

25 Based on accurate, timely data Observe historical failure distribution, as estimated by the statistical Cumulative Distribution Function (CDF)

26 Which allows us to forecast Analyse periodic maintenance scenarios, based on historic cost patterns, and the CDF. Blue = mean result, Red = worst result, Green = best result. Dotted line is cost of doing nothing i.e. 100% Breakdown Maintenance strategy.

27 Against very specific KPIs Drill down to particular Root Cause codes to discover that for some assets, any maintenance regime is better than doing nothing

28 To support decision making but for others, running to failure is better than any planned maintenance at all

29 And even best method modelling Model year-on-year asset TCO against residual value to optimise Preventive Maintenance schedules

30 We can also apply Criticality Ratings Asset Criticality provides a methodology to apply a standard risk assessment to assets either individually or by classification so that Mainpac 2011 calculates whether these are business critical assets or not

31 And Recommended Maintenance Strategies The Maintenance Strategy Tool uses a Reliability Centred Maintenance-derived decision tree to recommend the most appropriate maintenance strategy for assets either individually or by classification based on the consequences of failure

32 So, Automation and Asset Management 1. Be ruthless in working through the ROI for your terminal 2. Recognise that automation for Asset Management purposes generates a lot of data 3. Be prepared for very detailed transaction mapping, down to field level and including data transformation 4. Start simple and work out We ve been automating Asset Management in Manufacturing and Mining for years. If you are methodical and meticulous, your project has every expectation of being successful.