2010 Lean Mining

Int. J. Logistics Systems and Management, Vol. 6, No. 3, 2010 279

Copyright © 2010 Inderscience Enterprises Ltd.

Lean mining: principles for modelling and improving processes of mineral value chains

J.G. Steinberg* and G. De Tomi Department of Mining and Petroleum Engineering, Universidade de São Paulo, Av. Prof. Mello Moraes, 2373, SP, Brazil Fax: 55 19 32322248 E-mail: [email protected] E-mail: [email protected] *Corresponding author

Abstract: Most traditional extractive processes present stages that need modernisation and optimisation for enabling mining companies to warrant the effective achievement of both product quality and quantity. Such warranty, which is difficult to sustain due to the intrinsic nature of geological uncertainty, can only be achieved through an increased efficiency in the mineral supply chain. The paper demonstrates the benefits of creating models of existing mineral supply chains to identify and understand the points of value creation and places for possible improvement interventions. It shows how to identify a robust and risk-controlled path for the mining industry to benefit from the ‘lean thinking’ approach, introducing the concept of lean mining.

Keywords: lean thinking; process modelling; lean mining; logistics.

Reference to this paper should be made as follows: Steinberg, J.G. and De Tomi, G. (xxxx) ‘Lean mining: principles for modelling and improving processes of mineral value chains’, Int. J. Logistics Systems and Management, Vol. x, No. x, pp.xxx–xxx.

Biographical notes: J.G. Steinberg is a PhD student in the Department of Mining and Petroleum Engineering at Universidade de São Paulo, Brazil. He received his Bachelors of Engineering in 2003 from Universidade de São Paulo, and his MSc in Transportation Engineering, in 2006, from Universidade Estadual de Campinas. His research interests are in the areas of supply chain management, mining engineering and modelling and optimisation methods.

Giorgio de Tomi holds a position of Associate Professor with University of Sao Paulo, at the Department of Mining and Petroleum Engineering. He is also a member of the Board of Directors of Devex Technology, a worldwide technology supplier for the mining industry and previously has been a Group Director of the Datamine group. His research interests are in mine planning and scheduling, and the application of geostatistics for the optimisation of mining operations. He has graduated in Mining Engineering in the University of Sao Paulo, Brazil, and has received an MSc from Southern Illinois University, USA, and a PhD from Imperial College, London, UK.

J.G. Steinberg and G. De Tomi

1 Introduction

Over the last decades, but especially since the turn of the new millennium, the mining industry has drawn global attention for its strength and growth rates that have been following economics trends of developing countries such as Brazil, Russia, India and China (BRIC). Despite of the sector advances, mining still faces problems that are intrinsic to its activities and challenges brought by modern techniques of management, from which it has been detached for long time.

The exuberance of financial results from mining companies all over the world seems to be part of a much bigger phenomenon. Brazil owns some of the biggest natural deposits of both metallic and non-metallic ore in a planet eager for this kind of raw materials. The Asian demand, China’s in particular, has raised international prices of metals to impressive all-time standards.

According to Paul (2006), the London Metal Stock Exchange registered raises of 382% in Nickel prices, 323% in Copper prices and 280% in Zinc prices over the previous four years. Iron ore, Brazil’s top exporting item, almost doubled its price in 2007. Paul (2006) also states that economists and experts expect the market conditions to be maintained at least until 2010. Such escalation of metal demand and prices explains the increase of 54% in Brazilian’s mineral production from 2002 until now. BNDES (Brazilian National Bank for Economic and Social Development) projects that the mining industry will invest at least US$ 24 billion in the exploration of new Brazilian ore deposits until 2010 (www.vale.com). This statement only supports a recent announcement made by Vale (www.vale.com) where the company says it plans to invest more than US$ 59 billion until 2010 in organic structure and new mining operations.

In another study, Malhotra (2001) suggests that the responsible use of mineral resources is providing developing countries with a considerable number of opportunities for poverty reduction and economic development. However, current practice seems to indicate that such countries, including Brazil, do not always have proper mechanisms in place for balancing opportunities against risks whenever environmentally and socially correct initiatives are to be addressed.

In such highly competitive global market conditions, and especially when the world markets cast their eyes onto Brazil’s ore production, the local mining industry has initiated a general effort to restructure its productive processes to align them with new production techniques and paradigms.

Companies in general are commonly valued according to standards associated with productivity, as income and expenditure. The same principle applies to the mining industry, but coupled to these general economic indicators, mining business valuations also take into account additional risks for dealing with the unknown. The mining industry is inherently heterogeneous because of the variety of products exploited, grades, markets, and, most importantly, size of its companies, but it does have a number of similarities amongst its competitors. For instance, regardless of the market being serviced, these companies continuously seek competitive differentials to increase their profit margins.

Coulson illustrated the perception of value within the mining industry: “When began his career in a gold mining company, a young engineer was asked what the mission of that company was. Quickly he replied: ‘extract and produce gold’. He was wrong; the extraction and production of gold were not the goals of the company, but the means to achieve it. The real purpose of this and all other companies is to return money to their investors.” (Coulson, 2004)

Lean mining: principles for modelling and improving processes

The mining industry intensively uses its capital investments, working continuously within a high degree of financial leverage, with large investments to obtain large revenues. It is also a high-risk activity, since a mine plan is based only on estimates, and there is never a complete certainty of the quantity or quality of the ore available until the final depletion of the deposit. Vale (www.vale.com) confirms this situation through a company statement where the company executives announce that after reaching the first billion ton of ore from the Carajás district, the mine still has proven and probable reserves of 2 billion tons of ore. However, the geological reserve, according to the National Department of Mineral Production (DNPM) is much greater than that, potentially as big as 17 billion tons. Thus, mining operates under permanent uncertainty conditions and it requires not only proper business planning and analysis, but also a certain degree of faith in committing significant capital investments to start a new project.

This uncertainty-driven environment clearly emphasises how valuable is the structured and steady acquisition of production information within the mineral value chain. Initiatives such as production process modelling and analysis provide appropriate knowledge for mapping out and assessing the behaviour of key variables in the process from extraction at the mine face all the way down to sales and delivery of the ore products. According to van der Zee (2007), a challenge in simulation modelling is to produce models that are transparent, that is, facilitate stakeholders in validating and understanding key decision variables, their workings, and model output. Unfortunately, many simulation models tend to be less transparent, being influenced by the analyst’s mental reference models and simulation software libraries. Only the tight control of productivity, ore quality and mining costs given by models can balance the inevitable losses incurred by the uncertainties steaming from geological data.

The competitive advantages sought by shareholders and investors within the mining industry may be realised as technological innovations, quality and delivery assurances, or even as costs reductions through process reengineering. Traditional mining processes for extracting metalliferous minerals, fossil fuels and industrial minerals incorporate various stages and activities that require modernisation and optimisation so that ore quality and quantity of the products sold by mining companies can be properly managed. According to Chow et al. (2006) in recent years, the restructure of the customers’ supply chain and logistics network has redefined the way a logistic service is operated. Despite of the development of various kinds of logistics information systems to store and process all sorts of data and information to support daily logistics operations, the logistics planning or decision-making of logistics activity is still executed manually.

This desired quality assurance can only be achieved through a structured effort to modernise and so increase efficiency throughout the entire mineral value chain. Only then, mining companies will be able to maintain and maximise their competitiveness in global markets.

2 Literature survey

The research methodology used in this paper is based on the literature survey of both mineral logistics and all kinds of lean thinking theories and applications.


2.1 Mineral logistics survey

It is easy to picture the scenario of uncertainties and risks which the mining industry is immersed in. Uncertainties regarding size and grades of an ore deposit are initially addressed during mine feasibility study. US-SEC (2005) is an industry guide which provides a classification of ore reserves according to the level of uncertainty in its quality and quantity, ranging from indicated (or probable) reserves to measured (or proven) reserves. Ore reserves are defined as the portion of a mineral deposit, which could be economically and legally extracted or produced at the time of the reserve determination.

Measured reserves, according to US-SEC (2005) are the ones for which quantity is computed from dimensions revealed in outcrops, trenches, workings or drill holes, and grade or quality are computed from the results of detailed sampling. The sites for inspection, sampling and measurement are spaced so closely and the geologic character is so well defined that size, shape, depth and mineral content of reserves are well established. Indicated reserves are expressed as those for which quantity and grade or quality are computed in a similar way to that used for proven (measured) reserves, but the sites for inspection, sampling, and measurement are farther apart or are otherwise less adequately spaced. The degree of assurance, although lower than that for proven (measured) reserves, is high enough to assume continuity between points of observation.

Measured reserves represent the best estimate of ore quality and quantity in the mineral deposit that is being assessed. According to Pereira (2003), the estimation error for measured reserves can be up to 20% in relation to actual amounts of ore and for indicated reserves, it can be as high as 40%.

Even if the entire scenario projected presents itself completely faithful to reality, there are other kinds of risks associated with the mining activity, especially with the maintenance of stable operational processes. It is a key premise of a well constructed and managed supply chain for its operational stability. According to Craighead et al. (2007), supply chain disruptions and the associated operational and financial risks represent the most pressing concern facing firms that compete in today’s global marketplace. Extant research has not only confirmed the costly nature of supply chain disruptions but has also contributed with relevant insights on such related issues as supply chain risks, vulnerability, resilience, and continuity. Supply chain disruptions are unavoidable and, as a consequence, all supply chains are inherently risky.

These difficulties only reinforce the need of modelling existing supply chains. Robinson (2007) says that conceptual modelling is probably the most important aspect of a simulation study, and it is also the most difficult and least understood. Over 40 years of simulation research and practice have provided only limited information on how to go about designing a simulation conceptual model. According to the researcher, the four most important requirements of a conceptual model are: validity, credibility, utility and feasibility and it is extremely important to develop the simplest model possible respecting predefined key variables.

Modelling also allowed, besides protecting from risk, the selection and implementation of convenient deals with each specific supplier, knots on the mineral value chain, protecting the supplier if needed, aligning him to serve specific market needs, or market and companies strategies (Marquez, 2004).

van der Zee and van der Vorst (2007), states that owing to its inherent flexibility, modelling is often regarded as the proper means for supporting decision-making on


supply chain design. The ultimate success of supply chain modelling, however, is determined by a combination of the analyst’s skills, the chain members’ involvement, and the capabilities of the simulation tool. This combination should provide the basis for a realistic simulation model, which is both transparent and complete. The need for transparency is especially strong for supply chains as they involve (semi)autonomous parties each having their own objectives. Usually, these parties are represented by multimodal logistics channels. Mutual trust and model effectiveness are strongly influenced by the degree of completeness of each party’s insight into the key decision variables. Ideally, visual interactive simulation models present an important communicative means for realising the required overview and insight.

Unfortunately, most models strongly focus on physical transactions, leaving key decision variables implicit for some or all of the parties involved. This especially applies to control structures, that is, the managers or systems responsible for control, their activities and their mutual attuning of these activities. Control elements are, for example, dispersed over the model, are not visualised, or form part of the time-indexed scheduling of events.

Mineral supply chains are usually multimodal chains. The balance between the origin where minerals naturally occur and final consumers of processed minerals is maintained through several logistical channels and knots that transport, store and deliver using ships, trucks, trains, warehouses and many other logistical modals and facilities. By adopting multimodal logistics, companies can significantly reduce lead time and inventory carrying costs, which may constitute major improvements in both profit and customer service (Grasman, 2006).

2.2 Lean thinking survey

The lean literature survey researched many kinds of texts from theoretical approaches focused on manufacturing processes to practical papers on applying lean concepts to different areas of the market.

According to Morgan (2005), the lean thinking is based on a single principle: All forms of waste should be identified and eliminated. This seems simplistic but it is not because recognising true areas of waste is difficult. To identify waste, the ideal processes must be defined first, and then compared with the actual processes to determine their efficiency.

The lean philosophy utilises a bottom-up approach, which means that workers are empowered to create and manage their own portion of business processes. This approach is essential for creating and improving business processes that are large and complex but still efficient. Applying its concepts results in the most efficient and profitable business processes such as those used with great success at Toyota Motor Corporation is considered the world’s most efficient automotive manufacturer. Drawing on Toyota’s success in manufacturing, the lean thinking can also be applied to different types of businesses with similar, dramatic results.

Companies do not seek only to implement all these improvements, they seek to maintain it in a sustainable basis. Mann (2005) says that the lean management system consists of discipline, daily practices and tools to establish and maintain a persistent, intensive focus on processes. It is the process focus that sustains and extends lean implementations. Little by little, almost unnoticeably, lean culture grows from these practices as they became habitual.


In lean systems the results certainly matters, but the approach of achieving them differs sharply from conventional management methods. The difference in a lean management system is the addition of a focus on process, as well as a focus on results. The premise is that when designing a process the designer should seek to produce a specific result. If the job is well done, the results must be achieved. In concept, this is simply a matter of maintaining production at task time. If this is done, the demand is satisfied. As improvements in the process are made, improved results should be expected.

Six Sigma, as the operational lean tool focused on drastically reducing defects was also used to propose improvements in mineral value chains. Devane (2004) states that lean manufacturing and Six Sigma are two powerful process improvement disciplines that provide a set of tools, methods and principles to improve processes that meet or exceed customer requirements. The ultimate goal of any improvement initiative is to provide products or services of high quality to customers when they require them at an affordable price that would result in a profit for the provider.

Lean manufacturing and its most powerful tool, Six Sigma, support this high-level goal. Six Sigma provides an advanced statistical toolkit and a management system that focus on reducing output variation by controlling inputs and virtually eliminating defects. Lean provides principles and simple tools that focus on eliminating waste, increasing speed and increasing throughput.

3 Logistics concepts

3.1 Supply chain management benefits

The supply chain is the physical-space representation of points of origin and destination of goods, as well as its flow and other relevant aspects, to allow the viewing of the logistic system as a whole. That is, a number of nodes (points of origin or destination) should be linked through connections (means of transport) in pre-established quantities, as defined by Novaes (2000). The reengineering of supply chains in traditional enterprises and even the improvement of logistics channels in pre-existing chains have brought great benefits to companies that have committed investments in logistics over the last few decades. Whether in the form of processes’ cost reduction, increased quality of products and services or increased productivity, the graphs below show how many businesses have achieved significant differential through the re-evaluation of their supply chains.

Figure 1 illustrates how businesses have improved their supply chains by reducing costs with proper inventory and storage. Producers have streamlined their operations to hold fewer inventories. The inventory-to-shipments ratio dropped markedly during the 1990s and is now near its all-time low. In essence, new technologies have allowed firms to replace inventory with information and then use that information more productively. In many cases, stockpiles and warehouses are just an expensive insurance mechanism against the uncertainties of the supply chain, to balance out eventual fluctuations in demand. However, they end up overloading the overall production costs by bringing a wide range of ancillary costs such as losses incurred by items damaged and goods not sold or obsolete.


Figure 1 Inventory management continues to improve (see online version for colours)

Source: www.census.gov

Figure 2 shows logistics costs have trended downwards, from about 16% of GDP (Durable goods list) in 1981 to around 8.5% in 2003. Transportation costs have declined by nearly 25%, whereas inventory carrying costs have declined by more than 65%. Logistics costs have declined primarily because inventories are managed more efficiently: warehousing expenses have been reduced, and risks have been minimised as third-party providers increasingly furnish specialised and customised logistics solutions that are more efficient.

Figure 2 Logistics costs continue to fall (see online version for colours)

Source: www.bea.gov

According to Taylor (2005), problems in the supply chain have devastating effects on companies’ financial sector. Nike, for example, in 2001 estimated losses of $ 100 million by logistic problems. Several other companies also reported losses due to lack of a well-structured supply chain. A properly addressed supply chain usually results in a competitive advantage for any company, making it competitively strong. There are several examples of companies in the world that needed to change its supply chain to remain in the market. Siemens innovated and reduced the delivery time of equipments


from 22 weeks to only 2 weeks. Gillette was another company that registered a reduction of $ 400 million in inventories. Chrysler also needed to improve its supply chain in the 1990s, resulting in a net annual economy of over a billion dollars. The reduction in costs coupled with improved supply chains allow companies to benefit enough to cause a turnaround in the structure of the entire industry it is immersed in.

Well managed supply chains can bring huge success to corporations, but on the other hand, supply chain structures with disabilities can bring catastrophic results. Transporting goods is expensive, and any slight change in the supply chain has a major impact on the success of the operation. Customers are indifferent to the difficult negotiations on the supply chain. It is irrelevant to them for any decision being taken in the chain. The important thing to them is how to choose the best product at the lowest price. To have this product with the lowest price, companies must work together; manufacturer, distributor or retailer are all related and must seek to bring quality together.

Despite of the global advances in the logistic area, the mining sector still has much to benefit from the application of modern techniques of management in supply chains, and this is the main issue of this paper. Through research and innovation, the objective is to present the mining industry with challenging solutions from the logistics perspective. Management is to be encouraged to understand their supply chains and to establish efficient mechanisms to improve their productions processes wherever and whenever necessary.

3.2 High-performance supply chains

With a stable and running supply chain, the focus should be on advancing the frontiers of efficiency, obtaining satisfactory results without abrupt changes. A simple way to achieve this progress is to accelerate the flow of products in the chain, reducing time-cycles. Quicker modals are also a good option to increase speed when possible. There are cases when it is necessary to restructure some processes, applying lean thinking concepts.

A crucial point when designing high-performance supply chains is the queue management. If unable to restructure operations to eliminate these queues, operations that feed all knots of the chain must be delayed. Following the lean philosophy, activities that do not add value to the product should be removed and tracking systems, which help monitor and identify the movement of thousands of products for the chain, are commonly being implemented. Any slowdown in the chain can be easily identified with these technologies and they improve the information flow in the supply chain.

Another way to advance the frontier of efficiency is the centralisation of risk. According to Taylor (2005), the centralised inventory should, for example, cause a positive effect in reducing the costs of inventories, usually in up to 35%. To make transhipments also brings benefits to the chain. This technique is an option to lower inventories, because many facilities have electronic access to the stock of one another. This allows Distribution Centres (DCs) to deal with shortages, guaranteeing consumers the products they want because they are available at another store. There is also the possibility of making direct delivery of larger orders, where products go directly from central warehouses to retail stores, without passing by regional warehouses. Many costs can be reduced this way. This centralisation of risk may be difficult to manage, but well managed, and with investments, this strategy may benefit the whole chain beyond the reduction of costs.


Since 1980, production efforts were concentrated in designing products that are easy to manufacture. Nowadays, this effort covers the entire supply chain, because the manufacturing process emerged from within the factories. There is a homogenisation of manufacturing today, such as sources 110 or 220 volts. This standardisation is also seen in new products, where components can be used in various configurations depending on the consumer. The products are currently designed to reduce inventory and maintain the presentation. For example, baskets of gardens can be stored embedded in each other, reducing space required for storage at the store.

The most exciting innovation related to logistics and the design of products is the technique of postponement of differentiation. This technique is applied nowadays in the mining industry. A large factory, or in the mining case, the mine itself, produces generic products. These products will only be customised when they are in DCs near to their final consumers. It is a very useful management tool for products that are delivered throughout the world and manufactured in one place. This technique brings many advantages because it reduces the security inventory and increases the economy of scale. With this technique, the DCs must be adjusted to the idea of becoming involved in final assembly of goods, with machines, personnel and space. The postponement may be so great that reaches the house of the final consumer, such as in the cases of home theatres and bicycles configured specifically for a consumer. In the mining business, the final consumer can be considered the final shipment of mineral in the grade specified by the consumer. The mineral is usually blended in the harbour to meet the standard required by each buyer, mixing minerals from different mineral origins, ages and compositions.

This technique and several others implemented during the modelling and improvement of the supply chain can place any company in charge of its supply chain, but the invention of new techniques is the most guaranteed way to turn a company into a legitimate leader of the market.

4 Process modelling and improving

4.1 Modelling methodology

The mineral value chain is very specific and particular to different ore products. Therefore, each manager should identify an appropriate methodology for modelling the supply chain and processes dynamics of his own particular mine. On the basis of the concept of comprehending first to improve later, the challenge is to develop a technique for converting spreadsheets data and activity flowcharts into a realistic model of the activities performed at each mine in particular.

Owing to the large variety of activities within the mining sector and the different characteristics of the material depending on the mine it is being extracted from, it would be challenging to identify a universal model which would fit in all types of mines.

After acquiring proper knowledge of the facilities and logistic channels that compose the mineral value chain, management should focus on the second part of the process, which deals with optimisation and best practices already used in other industries, and how best to apply them to the mining industry. Processes are analysed and decisions are to be made on implementing, excluding or optimising processes whenever necessary. Priority should be assigned to the mining process areas related to logistics, such as haulage, stockpiling, storage, orders processing and information flow.


4.2 Improvement methodology

The improvement process should be implemented in such a way that it is incorporated in future events such as the design of new facilities, fleets and routes, or even in design of supply and distribution channels within mining companies. It should address moving trends of equipment, materials and people, seeking to identify opportunities.

Proven procedures and strategies used in the global industry should be implemented in mining modern businesses. According to Maximiano (2002), from the beginning of the 20th century until the mid-1970s, the industrial world was dominated by organisational concepts and techniques popularised by the expansion of European and US companies. Many mining businesses, which were mostly from British origins, also followed these administration paradigms.

In the transition to the 21st century, the Japanese administration model has been established as a significantly improved version of the techniques and the western proposals on administration. This model has become a universal standard and one of the main pillars that support competitiveness in the globalised economy. Nowadays, companies seeking to modernise their supply chains look at the Japanese administration model for reengineering their production processes. This model has been chosen as the basis for the proposed modernisation of the logistics processes within the mining industry introduced in this paper.

The Japanese business strategy is also known as ‘lean thinking’. According to May (2007), this term is used to identify a business philosophy based on the Toyota Production System that looks in detail the basic activities involved in business and identifies points of value creation and value reduction from the perspective of customers and users. The lean thinking approach involves the creation of continuous flows and pulled systems based on the actual demand from the customers. The value flow is then analysed to identify ways to improve it not only in the production plant but also through the entire supply chain, from raw materials to finished products.

The lean thinking approach aims to develop products that represent solutions from the customer point of view. The adoption of this philosophy has brought extraordinary results to companies that have applied it in practice. Table 1 here shows a few examples of how the new lean thinking concepts review previous business practices, often rooted deeply in the processes of most mining companies.

The Japanese approach introduced revolutionary concepts such as “Just in Time”, which ensures that inventories in production systems arrive exactly when needed, reducing stock volumes. It also introduced other techniques to reduce waste and increase quality, the two fundamental pillars of its theory. Lean thinking has also incorporated concepts from other administrative schools, such as “Six Sigma”, which was originally developed at Motorola. According to Pande (2001), this technique of quality control is a tool to further improve processes that are already under control on a continuous improvement cycle.

Results generally involve an increase in the capability of the company to offer products that customers want, at the time they need it, at the price they are willing to pay for, with lower costs, higher quality, shorter lead times, thus ensuring a higher level of profitability to the business. Developed originally in a production environment of the manufacturing industry, lean thinking has been applied, with significant improvements, to a large number of different industry sectors, such as automotive, aerospace, electronic, services, construction and health companies.


Table 1 Lean thinking transforming old practices

FROM TO

Compliance Exclusive focus on efficiency. Posture: “I can live with that”. Changes are not needed

Commitment Commitment and engagement with the process of cultural change

Complexity Guidance for perpetuating complex processes and accepting losses in the value chain

Simplicity An orientation for processes whose success is measured by its speed and simplicity

Tolerance with the error Acceptance of a certain margin of error and a consequent undisciplined corrective actions taking

Elimination of error Six Sigma is a constant goal in everything that is done. Guidance to raise the Sigma level of processes

Weak measures Financial measures incomplete or ambiguous; without inspection process of the impact on business results

Strong measures Financial measures solid, documented and aligned with the results of the business; formal monitoring system for the projects development

Analysis Departmentalisation of operations. Passive resistance to changes and virtual impossibility of success in multidisciplinary projects

Collaboration A collaborative mentality, and an informal standard pattern of discussion and debate of multidisciplinary projects

Impatience Urgency style. Attack the less important and short-duration benefits. Declaration of premature victory over results

Discipline Focus on the long term and sustainability of the results. Discipline in the method

5 Modelling the mineral value chain

5.1 Assembling a logistic network

The initial step for modelling and improving the mineral value chain is mapping out all of the processes that the ore is subjected to from the mine face all the way down to the customer. The focus of this activity should not only be the technological processes of ore extraction, but also on the logistics-related processes. All transportation and haulage channels must be reviewed, including the mine’s ore production, equipment and personnel, as well as the methods of storage, location and functionality of the warehouses. Another important activity is the mapping out of virtual channel processes, such as the data flow through the mineral value chain, which reflects how the production reacts to the demand.

The assembly of a logistic network begins with the definition of the sites and facilities that compose it. The initial task is the identification of the plant where major physical and chemical transformations occur. In the mineral value chain, this is normally the ore processing plan. The processing plant establishes the supply channels, immediately before and the distribution channels, immediately thereafter it. The processing plant is the heart of the logistics network and activities such as purchasing, marketing, HR, finance, administration and logistics are structured around it.


As far as the supply channels are concerned, the priority should be mapping out the primary suppliers. In a mine, this normally means the geological deposit, which is the source of the ore, also known as ‘ROM’ (‘Run-of-Mine’). If the ROM undergoes transformations before reaching the processing plant, such as in crushers and screens, these unit processes are identified as secondary suppliers, tertiary suppliers, and so on. The channels that interconnect these facilities are then analysed according to their operational conditions, and according to the volume of material handled by them.

The distribution channels are located downstream from the plant and they represent the mechanisms to distribute the plant production. The facilities in this portion of the logistics network are usually processing units for resizing or repackaging delivery parcels in intermodal terminals, or simply intermediate warehouses. These represent DCs to regulate demand and to control the output of products. The channels that connect these DCs are analysed in a very similar manner to the supply channels. Figure 3 shows, in a simplified form, the conceptual sequential stages of the ore from the mine face down to the end customers.

Figure 3 Mining conceptual sequential stages (see online version for colours)


5.2 Virtual channels

As far as virtual channels are concerned, the challenge of properly deploying an ERP system for mining companies is also a key issue on this study. Mining companies have been facing difficulties to achieve the benefits normally provided by ERP systems, such as the unification of productive processes and integration of industrial sectors through a single information repository for the entire production chain. In Brazil, management systems and automated production control technology have become popular within our modern business establishment. Within the mining industry, several companies started a concentrated effort to deploy such management systems, which often incorporate practices and assumptions that do not necessarily apply to mining. This, allied to the fact that the technical data available is often not understood by professionals outside the mineral industry, makes diffusion, absorption and ERP-based management of information in mining rather difficult.

5.3 Mineral supply chain peculiarities

The significant diversity on the operational conditions of mining enterprises makes it very difficult for most mines to aim for a common standard even within the same company and it may generate undeclared internal disputes that hamper further interaction. This situation requires mine managers to establish creative initiatives to transcend the static, one-dimensional vision currently rooted quite deeply in the industry. Managers should apply innovative approaches to supervise and control the mineral value chain, to integrate information, production and individual skills to boost the company’s results, thus making it more valuable and competitive both domestically and internationally.

The benefits of applying technology to address the issues discussed earlier, as well as the difficulties of properly implementing it, should be examined at the same time as modelling the mining-oriented logistics channels. It is important to note that logistics channels, which are incorporated into a single-instance environment, such as ERP software, are clearly easier to model and analyse than those operating over multiple databases with inevitable information conflicts and lack of full data integrity.

Because of the high degree of heterogeneity in mining, and because the logistics channels vary from mine to mine and from ore to ore, it is challenging to attempt the establishment of a single standard for mining logistics networks. Hence, this paper is focused on proposing an innovative methodology for mining logistics network modelling, which may be applied to all kinds of mining enterprises.

6 Lean mining: applying ‘lean thinking’ to the mineral value chain

6.1 Mineral value chain

As soon as all processes in the logistic network are restructured according to the “lean thinking” approach, all activities that do not add value to the product by consumer standards should have been eliminated. Only then, the reengineered chain without useless movements, channels, and stages can be effectively called “mineral value chain”.


After the assembly of the model of the mineral value chain, the next step is to improve the logistic network by applying advanced managerial models. The starting point of lean thinking is the definition of value. Unlike popular belief, it is not the supplying company but the end customer who defines value. For final customers, value is associated to their needs. Companies should concentrate efforts towards determining and meeting the specific needs for their operations, and charge appropriate prices to ensure increasing profitability through continuous improvement of their production processes.

The ability to understand and manage the relationship between value and end customer needs is one of the major difficulties to implement the lean thinking methodology in mining. The conventional operating mode of the mining industry is to push high production regardless of demand and to store products as ready-to-go “commodities” at the ending nodes of the logistics channels. lean thinking focuses on demand-driven systems able to follow and react to shifts in demand.

For a successful lean thinking implementation, the management challenge is to provide appropriate fluidity to the value-adding processes and activities. This requires a change in the mindset of the staff involved with running the network, shifting from production-driven to a value-added decision-making approach. It is important therefore to expose the personnel that deals with the mineral value chain to sites and industries where lean thinking has been properly applied, and allow them the opportunity to apply the same principles to the mining activities, hence establishing a lean mining approach to the business.

The immediate effect of creating a value-adding, continuous production flow is the reduction of the design time of ore products and of the quantity of ore in inventory. The ability to develop, process and distribute ore products quickly means a higher degree of visibility and presence of such products in the market. Lean mining provides the company with a clear path on how best to meet the need of the end customers almost instantaneously and with a high-efficiency logistics solution.

The long-term success of Lean mining depends on the proactive participation of all the staff and decision-makers related to the production process. The search for continuous improvement towards an ideal state should guide all the efforts of the company. All participants in running the mineral value chain such as operators, assemblers, manufacturers, distributors and retailers should have a thorough knowledge of the production process as a unique, transparent system and they should be able to dialogue to continually seek better ways of creating value.

Sales of minerals are normally detached and quite independent from the production process and the logistics connections end up being limited to specific portion of the mineral value chain. Geological processes provide the estimates for the contents of the ore body and in some instances the geological information can be carried across the mineral value chain all the way to product sales. However, these are only estimates for the quality and quantity of ore, and because of that, the actual mine production will always differ from the geological estimates. The challenge for mining companies is to manage the discrepancy between the planed/estimated outcome and the mining operation results, and to ensure that the expected results are achieved at the end of the process. To address this issue, a number of mining companies have been applying the Six Sigma concept.


6.2 Six Sigma; The most powerful tool

The Six Sigma approach to quality control was first developed by Motorola in the 80’s as a way to optimise processes that were already under control but required further improvement. Its fundamental principle is to increase consumer satisfaction by reducing end product defects. Its final performance goal is to achieve processes and products virtually without defects (less than 3.4 non-compliant items on each million units produced) says Pande (2001).

The results of industrial processes can be typically represented by Normal or Gaussian distributions. As illustrated in Figure 4, quality control on the large majority results (99.99975%) is expected to fall between +/–6 standard deviations of the normal function. Each standard deviation is represented by the Greek letter δ (Sigma), and that is why the concept has been named Six Sigma.

Figure 4 Normal distribution and standard deviations

It is not easy to achieve a 6δ quality standard and deliver it to customers on a continuous basis. Non-compliant items are transferred through the production chain and end up multiplying themselves along the supply chain. For instance, if we take a simple example of four linked processes with 99% perfection each, the compounded quality control assessment would be as follows:

(0.99) × (0.99) × (0.99) × (0.99) = 96%.

Mining companies that apply the Six Sigma approach can only achieve success by not allowing a non-compliant item to travel along the productive stages, which is precisely the strategy that should be adopted for managing the mineral value chain. This requires a careful review of the various components of the production chain, and the identification of controlling stations that will not allow non-compliant items to be transferred between components.

The standard Six Sigma methodology, as Pande (2001) states, consists of the following five stages, which are also illustrated in Figure 5:

• DEFINE: Set improvement targets that are consistent with the client needs and with the strategy of the venture. For instance, grades and physical properties of the ore to be delivered to the end customer.

• MEASURE: Hold measurements on the processes in progress and collect relevant data for future comparisons. For instance, monitor cycle times and fluctuations of grade during loading and hauling.


• ANALYSE: Analyse data to identify what is related and what is coincidence. Determine what the correlations are and make sure that all factors were considered.

• IMPROVE: Improve and optimise the process based on the analysis of data.

• CONTROL: Check to ensure that any change in the system is corrected before it results in failure.

Figure 5 Six Sigma stages (see online version for colours)

6.3 Lean mining

The lean mining approach is based in a two-stage procedure: (1) to identify value and eliminate unnecessary unit processes, and (2) to improve the efficiency of the key processes aiming at high-performance goals. Six Sigma is therefore the key component for the second stage of the lean mining approach, as it allows management to minimise non-compliant items and to optimise the key processes of the mineral value chain. However, such a drastic change in the core of the productive process of the mining company requires a strong commitment towards educating and training the staff involved in the mining process. As recommended by the lean thinking strategy, management should continuously encourage and motivate employees to increase their level of awareness of the lean mining approach. Figure 6 shows an example of milestones in the lean mining learning curve.

Figure 6 Awareness levels through full lean thinking commitment (see online version for colours)


6.4 VALE mineral value chain example

As a global company, and one of the world’s largest mining firm, VALE is seeking to implement modern management techniques to its mines supply chains from many different products distributed around the world.

The Brazilian mine of Carajás, near the Amazon forest is located in the largest financially viable mineralogical site for metallic minerals in the world. Nowadays, there are several projects aiming to nearly duplicate the production and exportation of iron ore from the region. VALE implemented in its existing mines and will deploy in its new ventures logistics tools that even unconsciously adopt the lean mining concept.

To ensure the stable flow of goods along the supply chain, VALE designed its supply chains with high degrees of automation. Whenever possible, devices were implemented to ensure the transport of ore at high and constant flow rates. Two of these devices are LDCBs (Long Distance Conveyor Belts), which replace the off-road trucks in the transport of ore from the mine to the processing plant and articulated conveyor belts that launches ore into the vessels without the need to stop for repositioning lances. In the case of LDCBs, as shown in Figure 7, many problems associated with transportation by trucks for long distances in remote locations are avoided. This is achieved by creating a low rate of unavailability due to maintenance and high reliability in the operation. Irregular amounts of ore being transported generate an irregular procedure in the entrance of the crushing plant for process.

Figure 7 Example of a LDCB as the one used in Carajás, Brazil, designed and operated by Vale (see online version for colours)

Another example of lean concepts being applied in mining processes are the conveyor belts that feed ore in the holds of ships in ports. They gained the differential of being articulated and with dashes allowing its repositioning during the loading operation. Usually ships have multiple compartments of cargo, and when each of the compartments was full, there had to be an extra time to repositionate the conveyor belt for the next hold.


In the modern process adopted by VALE, the loading is continuous, since two spears alternately operate in parallel. At the same time as one loads, the other is repositioned ensuring stability in the transport of ore through the supply chain as shown here (Figures 8 and 9).

Figure 8 Articulated conveyor belt charging vessel (see online version for colours)

Figure 9 Ship compartments of cargo (see online version for colours)

7 Conclusions

Most businesses have reaped rewards from implementing modern administration strategies. lean thinking, one of such leading methods brought by the Japanese administration mentality, has been improving the way companies run their businesses, the way they define value and the way they treat their customers. The big challenge for mining companies now is to undergo the same evolution and to implement the lean mining approach to interact intelligently with their customers and to synchronise their actions towards the market requirements.


Over the last few years, mining has become a leading force of economic progress in developing countries such as Brazil. Mining companies have managed to increase their productivity rates to a significant degree but even if such results fill the eyes of those who look at them superficially, in most cases the actual production processes conceal an intrinsic lack of efficiency that requires a change of management and administration strategies.

Often the sequential processes that compose the mineral value chain have been repeated for many years without significant modernisation. These sequential processes are structured in such a way that most unexpected variations in quality and quantities are absorbed and diluted along the way. Therefore, the typical mineral supply chain incorporated various obsolete and unproductive processes that have to be reengineered to enable mining companies to reach a much higher degree of rewards. Lean mining delivers those results by encouraging management to get a deeper understanding of the key productive stages of the mineral value chain and the logistics channels that connect them. This promotes intelligent, market-oriented decision-making, moving away from the uncertainty-driven strategy of keeping large stockpiles of ore products stored along the way with significant value and working capital locked away.

Acknowledgements

The authors wish to acknowledge the advice and guidance provided by their colleagues at LAPOL/USP and the Int. J. Logistics Systems and Management technical reviewers in the preparation of this paper. The financial support by the research agencies FAPESP and CNPq is also acknowledged.

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