**1. Introduction**

Modern metallurgical installations such as steel plants and copper smelters require a range of plant sensors and process control systems to attain their highest efficiency. It is often stated that the levels of so-called "smart automation" today represents the fourth-generation industrial revolution (sometimes also called "Industry 4.0")—following the first, considered as the power generation and mechanical automation (early 1800s), the second as widespread industrialization (early 1900s), the third as electronic automation (starting 1950s), and, now, the fourth [1], benefitting from modern information and communication technology (ICT), as illustrated in Figure 1. Learning from history, it is well-known that if a plant does not remain up to date, taking advantage of modern but proven equipment and controls, then it lags its competitors. This paper discusses the application of techniques, sensors, and mathematical modeling that can support copper smelters in their endeavors to modernize their operations through data acquisition and, thus, remain competitive.

**Figure 1.** Representation of "Industry 4.0"—the 4th industrial revolution. Adapted from [1]. ICT: information and communication technology.

By way of background, copper smelters [2] are quite complex, with a number of individual high-performance operating units functioning together. Two of the key primary instrumentation and control needs in copper smelting today—and throughout history—are air (or oxygen) measurement and control and furnace temperature. In February 1956, a paper was presented at the AIME Annual Meeting in New York on the fine and well-recognized converter operation at the Noranda smelter (now Glencore Horne) located in Rouyn-Noranda, Quebec, Canada [3].

After describing how the production capacity at the fairly new plant increased over the previous two decades since the start-up (in 1927) by simply installing additional and/or larger units, the author discussed a major effort at further increasing production capacity that included the installation of reliable instruments for measuring both the instantaneous air flow and reporting the accumulated air blown over any given time interval. The significance and benefits of this new instrumentation (higher production rates) were subsequently described; of interest, the converters at this plant reached record or near-record air blowing rates in the industry at this time, reflecting the fact that it was one of the leading plants of the day. Of course, such equipment is mandatory today, coupled with the distributed control system (DCS) and advanced computer models to provide feedback for optimizing the operation.

Furnace temperature measurements at the time were made by an optical pyrometer mounted so that it pointed downward onto the molten bath. While generally reliable, it was often prone to dust and fume build-up affecting a clear sight line; unsmelted flux and other materials on the bath could also lead to low temperature readings. Some thirty years after the above noted paper [3], a new pyrometer instrument operated by sighting directly into the bath through one of the tuyères was described at the Copper 87 conference held in Viña del Mar, Chile [4]. During the discussion, the authors were asked about the cost of the new instrument. An indicative preproduction price range was given when the questioner loudly stated that he could buy "a Mercedes-Benz automobile" for the price mentioned, whereupon the authors responded that if the questioner installed one of these instruments at his plant, the profits he would make would allow him to purchase quite a few Mercedes! The point is that proper selection and use of reliable instruments for automated data acquisition and control are vital for a proper functioning plant to remain competitive, as the cost of sensors are comparatively modest.

In batch processes, such as steelmaking or copper converting, knowledge of the precise endpoint of the operation is extremely important for compositional control and optimization of the subsequent refining operations.

The Boliden's Rönnskär smelter, located at Skelleftehamn, Sweden, operates one of the best converter aisles in the world today, in the authors' opinion. They also pioneered the use of the ingenious Semtech Optical Process Control (OPC) sensor device for precise endpoint determination [5] to detect when the last of the iron was expelled into slag and, subsequently, when the last of the sulfur was expelled into the SO2 offgas. This instrument spectrometrically measures trace amounts of lead and copper sulfides and oxides in the offgas and signals when the level of sulfides starts to decrease, signaling the end of the batch [6]. The precise endpoint control saves significantly in processing time at Rönnskär in the subsequent anode furnace, thus lowering operating costs and allowing higher throughput.

In spite of the successful implementations of modern sensors at certain smelters such as Rönnskär, there is a general hesitance for copper smelters to adopt sensor arrays, as it is often unclear what the operational implications will be. Indeed, it is unclear what will be the series of changes that will be necessary so that the perceived benefits of the sensors will be manifest, and it is therefore difficult to quantify what will be the true impact of these new sensors. This paper presents a unified quantitative framework for copper and nickel-copper smelters, which integrate thermochemical modeling into discrete event simulations and is intended to assist in smelter reengineering projects that feature innovative sensors in consideration the Industry 4.0 paradigm.
