IT in Manufacturing


A balanced approach

October 2008 IT in Manufacturing

Asset-intensive industries such as chemicals, mining and food processing are characterised by sizable capital investments in machinery and equipment. Companies in these industries usually have a large maintenance budget.

Cost considerations

Maintenance is often the largest fixed cost (other than raw materials) in such companies. In a medium-sized chemicals plant, the annual maintenance budget could be 10% of the original capital investment. This ratio of annual maintenance cost to capital investment can vary significantly by industry and depend on many factors, such as plant age, the level of complexity and the amount of moving machinery, but in almost all cases maintenance costs are substantial and need to be carefully managed.

Poor maintenance can lead to unplanned breakdowns, which can have a major impact on production and service levels. This adds to the business criticality of an effective maintenance function, which therefore has to be seen as highly strategic to these companies.

As with all businesses, manufacturing companies have to make sustainable profits. During periods when production demands are high, businesses might be tempted to reschedule planned maintenance into the future. Other factors that lead to maintenance being delayed could include cost pressures in the company, or in the case of very old plants a decision could be made to minimise maintenance as the plant has reached end of life.

Informed decision making

In practice, when management ask questions regarding planned or scheduled maintenance, they are often flying blind. Despite significant investment in IT systems, the computerised maintenance systems generally cannot provide relevant information to help the business make informed planned maintenance decisions. The information that is required is a combination of cost, replacement value, historic reliability, and process criticality (if equipment should fail, how would this impact production and what is the probability of failure?). Clearly, this is a complex calculation, requiring not only a large amount of data, but a high level of data integrity and statistical analysis. Most importantly though, maintenance data without information regarding the actual role of the equipment in the production process is next to useless – yet most maintenance systems are implemented independently of production teams.

The problem with CMMS

Many plants use their computerised maintenance management system (CMMS) as a tool for improving the efficiency of the maintenance processes. The emphasis is on reducing 'wrench time'. Doc Palmer describes 'wrench time' as the proportion of time during which craftsmen are being kept from productively working on a job site by delays such as waiting for assignment, permits, parts, tools, instructions, travel, coordination with other crafts or waiting for equipment information. A well implemented CMMS achieves all these benefits by (for example) ensuring spares are available in the store, making available standard procedures and instructions for defined tasks, and providing equipment information and accurate maintenance history. Furthermore, a CMMS can help plan maintenance work accurately and reliably, and generating job cards or work orders automatically. But is this enough?

The problem with most CMMS implementations is that the system is focused on optimising maintenance in isolation. Other factors, such as the opportunity cost of breakdowns and lost production, are not taken into account. So for example, a minor piece of equipment such as a steam valve might have the potential to bring down the entire plant should it fail. Shutting down and starting up a process plant can be an expensive exercise – failures of this type should clearly not be a frequent occurrence. Yet the standard CMMS information such as spares cost, part numbers, maintenance costs and historical failures may not reveal the true role of this particular steam valve in keeping the plant running.

Key performance indicators

The industry has developed concepts such as overall equipment effectiveness (OEE) to help place equipment performance in the context of the business impact. OEE is a measure of availability (downtime), performance efficiency (reduced capacity) and quality (rework, scrap). However, several analysts have pointed out fundamental flaws with OEE as a measure of maintenance effectiveness. For example, performance efficiency could be as much a result of good performance of the production department as of the maintenance department. Separating key performance indicators (KPIs) of these different, often conflicting objectives, requires careful design of the systems and a comprehensive understanding of the underlying process and business.

Contextualised reasoning

For operations management, the solution is to use a balanced approach that makes sure that maintenance information is seen in the full context of the production objectives. CMMS systems that are implemented as standalone islands are not effective. Nor are so-called integrated CMMS systems of much use if the integration is purely with financial and procurement systems, as these systems are also usually segregated from the realities of day-to-day production processes. Effective CMMS systems therefore need to relate production information with maintenance and equipment information. Modern IT technologies make this possible through combining process information (from control systems, for example) with maintenance data, and combining all of this with contextual information from production technicians and artisans. This combined information approach is necessary for producing data that enables effective decision making.

A recommended best practice when implementing a CMMS system is to start by going back to basics and regard it as a strategic project with major business implication. The project needs involvement from the finance, production, maintenance and safety departments. All too often we see the CMMS system as simply an advanced electronic filing system belonging to the plant engineer. If this is the case in your business, then you may need to consider a re-implementation.

For more information contact Gavin Halse, ApplyIT, +27 (0)31 275 8080, halseg@applyit.co.za, www.applyit.com





Share this article:
Share via emailShare via LinkedInPrint this page

Further reading:

AI data centres, nature and innovation
Schneider Electric South Africa IT in Manufacturing
Artificial intelligence is driving unprecedented demand for data centre capacity, with liquid cooling now central to managing the heat generated by high-density GPU clusters. Schneider Electric examines how next-generation data centres can balance performance with environmental responsibility.

Read more...
How to navigate the high-stakes economics of AI infrastructure
IT in Manufacturing
Nearly 60% of data centre operators are expected to adopt liquid cooling within five years as AI workloads drive demand for higher rack densities. Understanding the full financial picture of liquid cooling, from capital investment to long-term operational savings, is now essential.

Read more...
Protecting the digital mine
RJ Connect IT in Manufacturing
As mining becomes increasingly connected and automated, cyber threats are emerging alongside the benefits of digitalisation. RJ Connect and provides rugged networking, edge computing and cybersecurity technologies from MOXA to help protect critical mining operations from evolving attacks.

Read more...
SICK launches AI-powered 3D quality inspection
SICK Automation Southern Africa IT in Manufacturing
SICK has combined deep learning with 3D height data analysis in its Nova machine vision platform.

Read more...
Predictive maintenance is the critical enabler for AI data centre liquid cooling systems
IT in Manufacturing
As liquid cooling becomes essential for AI data centres, predictive and condition-based maintenance are emerging as critical enablers of thermal stability. Schneider Electric argues that the infrastructure is already generating the data needed and the question is whether operators are equipped to use it.

Read more...
Siemens software scales with Simple Energy EV development
Siemens South Africa IT in Manufacturing
: Simple Energy, an Indian electric two-wheeler manufacturer, has expanded its use of Siemens Xcelerator software to manage complex vehicle variants and enterprise-level bills of materials, accelerating product development as its EV portfolio scales.

Read more...
ESG as a growth lever
RS South Africa IT in Manufacturing
Leading organisations are treating ESG not as a compliance obligation but as a practical tool for operational efficiency, supply chain resilience and business performance, with data and collaboration central to unlocking its value.

Read more...
Preparing Africa’s data centres for the demands of autonomous AI
Schneider Electric South Africa IT in Manufacturing
Africa’s data centre infrastructure must evolve significantly to support agentic AI workloads, with GPU-intensive computing, advanced cooling and reliable power demanding a fundamentally different approach to facility design and investment.

Read more...
Virtualising the control room to reshape building management systems
Schneider Electric South Africa IT in Manufacturing
Schneider Electric explains how virtualising building management systems frees facilities teams from ageing hardware, delivers stronger cybersecurity and enables portfolio-wide control from a single interface.

Read more...
AI infrastructure solutions for data campus
Schneider Electric South Africa IT in Manufacturing
Schneider Electric and Motivair deliver more than $290 million in power and cooling infrastructure for TeraWulf’s AI-ready Lake Mariner data campus.

Read more...









While every effort has been made to ensure the accuracy of the information contained herein, the publisher and its agents cannot be held responsible for any errors contained, or any loss incurred as a result. Articles published do not necessarily reflect the views of the publishers. The editor reserves the right to alter or cut copy. Articles submitted are deemed to have been cleared for publication. Advertisements and company contact details are published as provided by the advertiser. Technews Publishing (Pty) Ltd cannot be held responsible for the accuracy or veracity of supplied material.




© Technews Publishing (Pty) Ltd | All Rights Reserved