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5 Steps towards Maximum Resource Efficiency Part 2: Material Flow Modeling, MFCA and LCA Made Easy

5 Steps towards Maximum Resource Efficiency Part 2: Material Flow Modeling, MFCA and LCA Made Easy

Last week, I introduced you to the first three steps small and medium-sized companies need to take to increase their resource efficiency to a maximum. Today, you’ll find the last two of the five steps involved in making the most use of material flow modeling.

Step 4: Calculate Product Costs Related to Material Loss

Broken down to one product, how much do my materials cost? That’s an appropriate question. In addition, material flow cost accounting can determine how much material is “lost” in every single process and every possible material cost. Viere et al.:

From the perspective of resource efficiency, any form of waste, undesired by-products, or even product outputs that need follow-up treatment or recycling, indicate inefficiency. A cost assessment of such inefficiencies is not trivial, though. While waste treatment and disposal costs are often known, these only account for the “tip of the iceberg”. Any form of material loss or inefficiency causes further and often much higher costs within the production system. Material flow cost accounting (MFCA) is a costing approach that focuses on the proper assessment of such inefficiency or material loss related costs.

How that exactly works, I showed in my recent MFCA article. Additionally, Viere, Stock and Genest illustrated the use of MFCA by employing a good example. They wrote that from the viewpoint of MFCA, wastes and remnants are treated “like products or cost objects”. So “costs are not only assigned to products, but also to material losses, usually in proportion to their mass ratio.” To fully understand the significance of the precise budgeting of material losses, read the following example from page 12 of Viere et al.’s PDF:

“Figure 10”: Material loss from combing process
“Figure 10”: Material loss from combing process

SWU’s combing process in WaIdkirch serves as an example […]. During combing, short cotton fibers are separated from the long ones, since certain product qualities can only be achieved with long fibered cotton. The combed out cotton fibers can still be sold as a by-product. The sales price normally is lower than the purchase price for cotton, though. With the assistance of a material flow cost calculation the material and energy flow based costs of the short fibers were calculated and confronted with the sales revenue of that remnant. Figure 10 and Figure 11 [see screenshots on the right] present the quantity based as well as the cost based evaluation.

“Figure 11”: Material and energy flow cost of 1 t of material loss from combing process
“Figure 11”: Material and energy flow cost of 1 t of material loss from combing process

Along the way from the receiving warehouse to the combing the cotton is passed through several process steps. Each of these production steps consumes energy and auxiliaries and generates waste that causes disposal costs. Consequently, to “produce” one unit of remnant, the costs for cotton, energy and disposal rise. The proceeds of the remnants can just partly compensate the losses, so that a net loss of roughly 500 € per t of remnant occurs. This loss would be even higher if further cost groups such as depreciation cost or labor costs are considered.

So far, so good. We’ve made a model and found good use for it. We now know how much energy and material our production consumes, how that relates to our product, and exactly how much the losses that occur throughout production cost. But what do we do with the latter? Losses will always occur, no modeling can prevent that. The very laws of thermodynamics say this. So what, again, is MFCA good for?

Obviously, the loss calculated by MFCA cannot simply be avoided. Nevertheless, its consideration offers an opportunity to reconsider decisions in terms of resource efficiency. For instance, the purchase manager of SWU can precisely calculate what kind of mark-up will be appropriate if a decision between cotton with a large amount of short fibers and high quality cotton with a smaller amount of short fibers needs to be taken.

Yeah, that makes sense. One model, three good uses. We have gained a valuable insight into our production, know what material goes which way, and know what the costs are. What more could we want? Well, despite the fact that, in the end, taking responsibility even pays off, corporate responsibility goes beyond cutting costs.

Step 5: Calculate the Environmental Impact: Life Cycle Assessment

With a little addition, our material flow network can serve as the basis to calculate the environmental effects of our production and our product. Life cycle assessment is the keyword. A gate-to-gate LCA, as in the environmental impact of transforming cotton (that arrives at the factory gate) to textile product (that leaves the factory gate), could be calculated right within this very model. A more complete cradle-to-gate or even cradle-to-grave analysis, however, would require the modeling of additional transitions. Our guide mentions “upstream and downstream transitions” and takes cotton production in Africa or product distribution as an example. Anyway, all you have to do is attach a figure for environmental impact to each of your material flows. Very probably, you won’t know this figure by heart, so it comes in handy that Umberto includes a big database containing thousands of values. Data availability is a big topic, though, because diverging data means diverging results. Umberto’s principal database is called ecoinvent, which is the Swiss Army Knife of LCA Background Databases, but the program can import any database you like. In this project, SWU did not conduct a full LCA. Instead, it chose a more basic approach by embracing one impact category only, the corporate carbon footprint:

[I]t is possible to conduct an environmental assessment by combining material and energy flows with data on environmental impacts. For instance, an ecological backpack of 1.3 kg CO2eq (carbon dioxide equivalents) could be assigned to each kg of cotton to determine its contribution to climate change. […]
“Figure 12”: SWU Corporate Carbon Footprint overview and details
“Figure 12”: SWU Corporate Carbon Footprint overview and details

In the case of SWU, life cycle assessment had been limited to a first rough analysis of the climate impact, considering both, the company and their products. Figure 12 shows some details concerning the company’s corporate carbon footprint classified according to the scopes defined in the Greenhouse Gas Protocol [13]: direct emissions in scope 1, energy-related indirect emissions in scope 2 and all further indirect emissions in scope 3. While data quality and reliability for scope 1 and 2 was considered as very high, data quality for scope 3 had been a more delicate matter. Life cycle data for cotton, for instance, varies significantly depending on the source or database used. At the same time, the carbon footprint value for cotton affects the overall results substantially.

1 Prerequisite and 7 Benefits of Material Flow Analysis

If I succeeded in making a point in this article, you hopefully now agree that material flow analysis is not easy, but not that complicated either. Viere and his colleagues pointed out that in order to work, it involves the full cooperation of the various departments, namely, top management, production planning, engineering, and, of course, accounting. In conclusion, they outlined the seven benefits that SWU enjoyed after going through all of today’s steps. All that I have to add is: Enjoy.

  • Better understanding of cost drivers: Hot spots in terms of material and energy usage can be identified easily. Particular important energy users like the air compressors or the ventilation system have been improved continuously.

  • Enhanced investment decisions: In the past, investment in more efficient spindles and motors in the spinning area had not been approved due to long amortization schemes. Considering the fact that more efficient devices produce less waste heat and hence reduce the demand for air ventilation and cooling, the amortization time came down to profitable levels.

  • Additional information for costing decisions: Material and energy flow related cost accounting provides new and precise information on inefficiency related costs and product specific cost differences.

  • Understanding of environmental relevance: Rough carbon footprint analysis improved the understanding of environmental consequences of products and production system and revealed major drivers of the company’s environmental performance.

  • External reputation and visibility: Figures and visualizations of energy and resource efficiency help to convince customers and business partners that SWU is managing the efficiency challenge well. Furthermore, the external certification of their environmental management system according to ISO 50001 was achieved smoothly due to the abundance of relevant information.

  • Development of an energy and resource efficiency “culture”: The improved understanding of the relevance of energy and resource efficiency improvements for the company’s success has initialized a change of mindsets within the company. For instance, accountants show interest in leakage measurements for compressed air as they are aware of the cost saving potentials.

  • Finally, the benefits can also be quantified: Up to know, SWU’s energy and resource efficiency measures have led to annual cost savings well above 100,000 € which is by far more than the company expected in the beginning. These cost savings have a large share in the company’s total profit.

Further Reading

  • Möller, A.; Rolf, A.; Page, B.; Wohlgemuth, V.: Foundations and Applications of computer based Material Flow Networks for Environmental Management. In: Rautenstrauch, C.; Patig, S.: Environmental Information Systems in Industry and Public Administration, Idea Group, Hershey, 2000, 379-396
  • Viere, T.; Stock, M.; Genest, A.; How to achieve energy and resource efficiency: Material and energy flow modeling and costing for a small and medium-sized company; ifu Institut für Umweltinformatik Hamburg GmbH; EnHiPro; 2013; PDF Download available, chapter 2-18 at qucosa.de

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