Why does raw material
management concern the
entire company?

Most projects aimed at improving raw material management can in some way benefit from each section and member of the company contributing to the stated goals. This starts in the scrap yard receiving material, through to the rolling mill sorting the internal scrap according to grade, and includes most of the workforce, from the individual craftsperson to the CEO.

Can you benefit from pooling in-house bodies of knowledge?

Settle for less than optimal?

Many companies are limited by a culture which has developed within the organisations over time, often unwittingly, whereby crucial knowledge and experience has become clustered in various departments of the company, bodies of knowledge. The level of competence in each department can be considerable but the lack of common models and practices can seriously hamper overall performance. One set of findings may appear beneficial to one department, but less so to another using the same data but other models. One example may be buying cheap raw materials and obtaining higher slag volumes, energy usage and lower productivity. Another may involve maintaining perilously low grade inventories forcing the use of premium materials when you have run out of what could have proven fully adequate for a specific process.

Reaching common understanding

Sharing a common model may allow people throughout the organisation to easier attain a common understanding of the overall costs and benefits to a plant.

Learning over time

Management of uncertainty is another challenging aspect that calls for a helicopter perspective of the production.
During day-to-day operations the variability of raw material properties makes it difficult to draw definitive conclusions from a limited set of
charges and to adjust the raw material usage accordingly. This kind of analysis is often better performed over a longer period of time and is preferably done by a dedicated team with a competent tool.

Providing reliable data

Finally, the strategic raw material management is dependent upon an organisation that can provide reliable and consistent data, successfully implementing the chosen models and deliver on decisions. Lacking this capability it becomes increasingly difficult to make decisions on inventory size, investments in raw material sampling, processing etc.

Boosting motivation

An overall culture of sharing information allows each individual to fully appreciate their specific role and value to the entire system.
This type of practise quickly translates into a host of benefits as each member appreciates that their contribution is valued.

Would it be conceivable to manage this level of complexity without models?

A number of factors affect the profitability of a metallurgical plant. These are all
interrelated and this simplified image contains merely a few examples of factors any scrap based metallurgy operation needs to take into account

Without models? Impossible!

Would it be conceivable to manage without models? No, of course not. Even without computers most people use mental models to help them make the day to day decisions. With computers however, a more complex reality can be handled and decisions documented, monitored and the decision-making improved.

As Einstein said: “A model should be as simple as possible but never simpler”. Even with a simple model the quality of data is crucial. Modelling work must always be preceded by implementing data acquisition and data refinement protocols.

No quick fixes

With increased competition, raw material scarcity and requirements for sustainable production, demands on the management of resources and production, has increased. There are no quick fixes for any of these realities, yet they do in fact all offer opportunities for everyone from the loader of the baskets, the shop floor manager and all the way up to the CEO of the company.

The “one more” cost factor

A common misconception is that “There are so many other production cost factors to optimize. What benefit could yet another one generate?”
The truth is that companies who strive to master raw material selection and optimisation, will also see corresponding knock-on improvements in other cost factors.

The winds of change are blowing

Using models for raw material management requires a consistent and easily accessible flow of good quality data. In almost every project throughout any company there is a piece of informatics involved which creates an opportunity to improve data accuracy and thus the ability to save money. These constitute Areas for Improvement.

New times – New working tools

It is our belief that introduction of new technology or new working tools must go hand-in-hand with development of the organization, practices and existing tools throughout the organization. If you want this to happen, prepare for an interesting journey, involving many small steps and spanning almost all development projects throughout the company.


Try again and succeed

When proposing the introduction of process models, optimization tools, or other changes, one of two arguments are frequently put forward: “We tried it and it did not work” or “Interesting but we simply do not have the time”.

Advances in models and the introduction of improved tools, have identified the need to adopt a company-wide approach to their implementation. Limiting the pool of people involved would also limit the effects of any changes made. The inclusion of not only all relevant parts of the organisation, but also making each participant in the change process privy to the goals and their benefits, means that it is now possible to achieve a critical mass – something which was previously unrealistic. Remember that Edison did not succeed with the lightbulb in his first attempt. What about the time factor? Well, it is our experience that the conscientious manager, no matter how swamped, always strives to find time to chart a course ensuring that the company develops consistently in the right direction.

Enhancing the raw material assessment tool RAWMATMIX® for EU users done with support from.