Short-term Production Research Articles

Resilient Decision Making in Open Pit Short-term Production Planning in Presence of Geologic Uncertainty

Short-term production plans are the basis for operational mine production schedules. They concentrate on making long-term mine plans operationally feasible. Furthermore, some variables such as ore grade and tonnage govern mine production systems and cause uncertainty in the supply of raw materials to the mills. Due to the quality variation of material, short-term production optimization is an uncertainty-based problem. Feed quality is a prerequisite for the mill designer. It affects the mill efficiency and the type of measures with respect to environmental regulations. There is a need to control and to predict the quality of feed at the mine site to meet mill requirements, which is a complex problem. To deal with this issue a stochastic optimization model is developed to capture the effects of resource uncertainties on mine planning. In that regard, three performance indicators are defined and an optimized mining schedule is used to simulate the performance of these indicators throughout the mine-life. This will quantify the effects of geological uncertainty on short-term and long-term plans. The objectives of the model also include minimizing the deviation of expected quality and quantity from the required values. The methodology was illustrated using a case study on a surface gold mine in Iran. This approach leads to resilient decisions and better quality control.

Stochastic short-term mine production schedule accounting for fleet allocation, operational considerations and blending restrictions

A new short-term mine production scheduling formulation is developed herein based on stochastic integer programming. Unlike past approaches, the formulation simultaneously optimizes fleet and mining considerations, production extraction sequence and production constraints, while accounting for uncertainty in both orebody metal quantity and quality along with fleet parameters and equipment availability, all leading to a well-informed sequence of mining that is expected to have realistic as well as high performance during a mine’s operation. To assess the latter performance and implementation intricacies of the proposed formulation, the formulation is applied at a multi-element iron mine and the resulting monthly schedules are assessed and compared to the conventional mine scheduling approach showing: lower cost, minable patterns, efficient fleet allocation ensuring higher and less variable utilization of the fleet.

Beyond sustainability. Transforming industrial zero-valued residues into increasing economic returns

Excessive industrialization is creating enormous economic gaps, chaos and unequal societies that are approaching dangerous limits. Simultaneously, large quantities of residues, waste and ecological footprints have been created in detriment to the natural environment and the quality of life of most of the planet's population, mainly in developing regions. This presents most innovators with a new dilemma: Invest in sustainable long-term projects with low economic returns, or innovate in short-term incremental production and negotiate the environmental harm caused by an excessive industrialization. In fact, a significant milestone emerges from these arguments. Somehow, we must reverse the perverse cycle created by industrialization and transform the current ecological footprint into valuable assets, for all sub-systems of the biosphere. A proposal has been designed to go beyond sustainability and create sustainable wealth, based on the modification of the conventional growth paradigm, that can be used to regenerate regional natural resources and simultaneously be economically competitive and capable of offering important social benefits to the community. The proposed framework, SWIT (Sustainable Wealth creation based on Innovation and Technology) has been developed to provide multiple businesses of zero-value residue industrial ecology processes (ZRIES), inserted into circular value ecosystems (CVES), all managed and governed by a sustainable sharing value system for the benefit of a community. Several cases of the application of the sustainable wealth creation framework, mainly in developing countries, are described.

A comprehensive assessment of agricultural intensification scenarios for the Dongting Lake basin in south-central China in 2030.

To explore the future of the material demand, pollutant emission, production, and arable land area surrounding the Dongting Lake basin, and to find a potential solution for agricultural development, this study assumes the following four agriculture intensification scenarios: the natural development scenario (ND), the production development scenario (PD), the moderate intensification scenario (MI), and the local resilience scenario (LR). The scenarios focus on different developmental patterns (natural development, short-term production growth, long-term sustainability, or self-sufficiency).The result shows to satisfy the food demand in 2030, and the production of crop and meat will be 26.96, 30.25, 28.05, and 16.27 × 10(6)t in ND, PD, MI, and LR, respectively; more than 1.78 × 10(6)ha of arable land is needed. Compared with the year 2012, the material input and pollutant output will increase by a maximum of 18.32 and 122.31%, respectively. By classifying the environmental risk into four categories-greenhouse gas emission, air pollution, eutrophication, and ecotoxicity-the composite environmental risk index (CER) is calculated. The CER in PD was the highest, followed by that in ND, LR, and MI. Due to the production allocation within the 35 cities and counties, the spatial distribution of CER is more homogenous in PD and MI than in ND. The analysis of the scenarios reveals that through technological improvement and spatial allocation of agricultural production, scenario MI could be a potential direction for the government to design a sustainable agricultural-environmental system.

Zero-point fixture systems as a reconfiguration enabler in flexible manufacturing systems

ABSTRACTToday's manufacturing systems need to be able to quickly adapt to customer demands, ranging from high volumes of mass production to high volumes of mass customization. Flexible Manufacturing Systems provide a high degree of flexibility to cope with these challenges. They consist of machine tools capable of executing a wide range of machining operations while the use of pallets to reference and block the parts allows the decoupling of the setup operations from the machining centers activity. This paper presents an ontology-based framework to support the design and management of flexible manufacturing systems, aimed at integrating the various involved activities including the pallet configuration and process planning, the management policies for short-term production planning and the pallet checking to verify the correct configuration of the physical pallet.

Comprehensive Study of Kisan Credit Card at Central Bank of India-A Useful Credit Tool for Rural Development

The KCC is pioneering credit delivery innovative products which provide a adequate and timely credit to farmers' thorough single window, with flexible and simplified procedure, adopting whole farm approach, including the short-term credit, medium term and long term credit needs of the borrowers for agriculture and allied activities and a reasonable component for consumption needs. The Government of India introduced KCC scheme by banks during 1998-1999. It was designed by NABARD. KCC aims at adequate and timely support from the banking system to the farmers for their short-term production credit needs in cultivation of crops, purchase of inputs etc in a flexible and as well as cost effective manner. Under this scheme, the appliers would be issued a credit card-cum pass book incorporating the name, address, particulars of land holding, borrowing limit, validity period etc and it will serve both as an identity card as well as facilitates the financial transactions. Credit limit of the card may be fixed on the basis of operational holding, cropping pattern and scale of finance as recommended by the DLTC&SLTC. As per the recommendations of Sri R.V. Gupta committee in the year 1998, on the flow of credit to agricultural sector, apart from the total credit need, a 20 per cent of total peak level credit requirement (PLCR) there is provision of contingent credit need (with a minimum ceiling of Rs.20,000). Normally The KCC should valid up to 5 years and subject to annual review. The KCC will be considered as a nonperforming asset (NPA) if it remains inoperative for a period of two successive crop seasons.

Achieving manufacturing excellence through the integration of enterprise systems and simulation

This paper discusses the significance of the enterprise systems and simulation integration in improving shop floor’s short-term production planning capability. The ultimate objectives are to identify the integration protocols, optimisation parameters and critical design artefacts, thereby identifying key ‘ingredients’ that help in setting out a future research agenda in pursuit of optimum decision-making at the shop floor level. While the integration of enterprise systems and simulation gains a widespread agreement within the existing work, the optimality, scalability and flexibility of the schedules remained unanswered. Furthermore, there seems to be no commonality or pattern as to how many core modules are required to enable such a flexible and scalable integration. Nevertheless, the objective of such integration remains clear, i.e. to achieve an optimum total production time, lead time, cycle time, production release rates and cost. The issues presently faced by existing enterprise systems (ES), if properly addressed, can contribute to the achievement of manufacturing excellence and can help identify the building blocks for the software architectural platform enabling the integration.

Routing of Mobile Resources with PSO using Chaotic Randomness (Chaotic-PSO) for Unexpected Delivery Failures in Manufacturing

Dealing with short term and long term production planning and scheduling has already been solved with different optimization and artificial methods and approaches. Under normal manufacturing conditions supply and demand progress controlled and supported by decision support systems, ERP and MRP software packages aiming maximum utilization of resources and minimizing the stocks aiming for JIT. These software packages becoming even more intelligent and proactive based on the data in the database systems. However all these systems starts with initial assumption of under normal conditions of flow time ordering to delivering. In case of unplanned stops, failures, malfunctions, shortages of unplanned inventory levels alters these initial conditions and progress to a diverging outcomes and consequences. This paper aiming a dynamic allocation and routing of mobile resources in a manufacturing plant by reallocating them by using a modified Particle Swarm Optimization using Chaotic Randomness

Truck-shovel allocation optimisation: a goal programming approach

Decision-making in mining is a challenging task. Optimal decisions regarding shovel and truck allocations, in consideration to the short-term production schedule, are very important to keep the operations inline with the planned objectives of the company in long term. This paper presents a mixed integer linear goal programming (MILGP) model to optimise the operations based on four desired goals of the company: (a) maximise production, (b) minimise deviations in head grade, (c) minimise deviations in tonnage feed to the processing plants from the desired feed, and (d) minimise operating cost. The model provides shovel assignments and the target productions; as an input to the dispatching system while meeting the desired goals and constraints of the mining operation. The model implementation with an iron ore mine case study provided average plant utilisation above 99%, average truck utilisation above 92% and average shovel utilisation above 95%.

Management of recycling operations for iron and steel making slags

Iron and steelmaking slags constitute important by-products of iron and steel production. Since slags are indispensable to iron and steel making processes, established recycling alternatives can be used to convert accruing slags to secondary resources, such as road construction materials, cements and fertilizers. The potential of a recycling alternative depends on a multitude of technical, economic and ecological influencing factors. In short-term production planning, the concurrence of these factors leads to the question how slags are to be recycled. The focus of this contribution is set on developing an adequate recycling planning approach based on techno-economic modelling. By combining activity analysis and flowsheet simulation, a modelling methodology is derived, which allows to model mechanical recycling processes characterized by particle size distributions. Further, management accounting and price functions are used to describe the occurring recycling costs and revenues for secondary resources, which are characterized by regional market structures. The developed concept is incorporated into a decision model, which is used in an illustrative example.

The geometallurgical framework. Malmberget and Mikheevskoye case studies

Geometallurgy is a growing area within a mineral processing industry. It brings together tasks of geologists and mineral processing engineers to do short and medium term production planning. Howeve ...

Customer-oriented Production System for Supplier Companies in CTO

Configure-to-Order (CTO) is one of the common market interaction strategies for suppliers. In CTO, the customer configures the product where bill of materials, drawings and working plans are elaborated automatically. Traditionally, the Order Penetration Point (OPP) is set too early which induces high costs of stock and long delivery times. For assuring short delivery times and low levels of stock, the supply chain should be triggered according to the customer demand.The paper presents an applied research project performed by a German medium-sized windows and doors production company, where a new customer oriented production system was developed and implemented. The main objective of the holistic production system is to allow a Just-in-Time (JIT) production of windows and doors with short operating costs. It is based on the CONstant Work In Progress (CONWIP) approach needed for assuring short delivery times. More in detail, it presents an approach for medium and short-term production planning needed for triggering JIT the first and second-tier supply chain. As a result, the paper presents design guidelines for production systems with short delivery times in the CTO-market interaction strategy.

Improving Data Consistency in Production Control

Under volatile market conditions, manufacturing companies, which achieve a high adherence to promised delivery dates, possess a considerable advantage over their direct competitors. However, due to dynamically changing production circumstances, this logistical target is rather hard to reach. Excellent production planning and control (PPC) processes are a main prerequisite for managing inevitable turbulences which occur in every production system and which impede to follow through with detailed scheduled production plans. An often overlooked reason for deviations between the originally planned and actually realized production program is the inadequate data quality of master and transaction data. PPC processes such as detailed scheduling, production control and production monitoring rely heavily on a vast volume of data in order to update short-term production plans, derive conclusions for ad-hoc control interventions and monitor resources’ efficiency as well as production job statuses. Typical techniques for dealing with inadequate data quality in the business context involve implementing integrity constraints in databases and defining data quality processes for the whole organization. Evidently, these classic approaches are not successfully preventing manufacturing companies from dealing with inadequate data quality in PPC processes. This paper presents a new approach for mitigating the negative effects of deficient data quality in production control by adapting data mining (DM) algorithms in order to estimate probable values for typical data inconsistencies in data relevant for production control. The algorithms are tested on a real-world data set of a typical mid-sized manufacturing company and their capability of retrieving the correct values is quantified.

APPLICATION OF OPERATIONS RESEARCH IN OPEN PIT MINE PLANNING AND A CASE STUDY IN SINQUYEN COPPER DEPOSIT, VIETNAM

Operations research has been applied to open pit mine planning since 1960s. This approach has proved its ability in optimising mine planning problems, including long-term and shortterm production scheduling, ultimate pit limit, mine design and mining equipment dispatching. In this paper, we review the history and methodology of applying operations research in long-term production scheduling and a case study in Sin Quyen copper deposit, Vietnam.

Method for an Energy-oriented Production Control

Increasing energy costs as well as a growing awareness for sustainability are challenging companies to use energy more efficiently. Therefore, a company's production planning and control strategies have to be adapted. This paper presents a method for a short-term production control which aims to synchronize the energy demand in manufacturing with a limited energy supply. The method treats electric energy as a limited production capacity where load profiles for manufacturing are predetermined and integrates load management into the production control in order to minimize energy costs.

Modelling Minimum Pressure Height in Short-term Hydropower Production Planning

When planning the production for certain hydropower plants, minimum pressure is one of the major critical points. Violation of the minimum pressure causes the power plant to automatically shut down, hence violating the obligations of the plant. Automatic pressure switches and pressure constraints are difficult to model in particular when embedded in a complex water way. This problem is expected to increase when retrofitting hydro installations with new parallel units and increased exploitation of inflow resources. From a scheduling point of view, however, such switches become hard to integrate in an optimal operation plan as the constraint depends on the system state. This paper introduces a novelty in short-term production planning, namely a solution for modelling minimum pressure height in regulated watercourses when optimizing the energy production of hydropower plants. This solution is integrated in the short-term hydropower scheduling tool SHOP. The tool finds an optimal strategy to run a power station with such minimum pressure restrictions and the state dependent topological couplings within the water system. We apply the model on a complex topology, the Sira-Kvina water system, where Norway's largest hydropower station Tonstad Kraftstajon is operationally subject to this rigorous pressure constraint. First, in order to illustrate the concepts of the model, we apply the model on a simplified water course including one reservoir. Next, the outcome and tests are demonstrated on the final model of two reservoirs whose respective outflows are joining together above the pressure gauge, as found in the Sira-Kvina water system.

Improving Data Consistency in Production Control by Adaptation of Data Mining Algorithms

Manufacturing companies are increasingly exposed to volatile market conditions. In this environment, ensuring a reliable adherence to promised delivery dates, allows for a considerable competitive advantage. However, due to dynamically changing production circumstances and high varieties in production programs, manufacturing companies regularly fail in reaching this logistical target. A main prerequisite for mastering this challenge are excellent Production Planning and Control processes. The quality of transactional data of production processes are a commonly ignored root cause for inadequate detailed scheduling plans although a vast volume of these data are used for updating production job statuses and short-term production plans, deriving conclusions for immediate control interventions as well as monitoring production efficiency. Typically, measures for improving data quality involve implementing integrity constraints in databases and setting up data quality processes as well as dedicated organizational structures. Evidently, these classic approaches do not successfully prevent manufacturing companies from dealing with inadequate data quality in their PPC processes. Consequently, this paper presents a model for increasing the quality of data relevant for production processes by adapting data mining algorithms. This new approach allows to estimate probable values for typical data inconsistencies in transactional data of PPC processes. Several adapted algorithms are benchmarked on real-world data sets of German mid-sized manufacturing companies and evaluated towards their power and efficiency.

California’s drought as opportunity: Redesigning U.S. agriculture for a changing climate

AbstractThe impacts of climate change are already affecting the production and profitability of agricultural systems, and these trends are expected to continue in the future. Without support from ecosystem functions, an agricultural system designed exclusively to maximize short-term production is vulnerable to extreme weather events such as droughts and floods. This results in high costs for farmers and ultimately for society at large, in economic and ecological terms. Complex agroecosystems that maximize biological interactions and conserve soil are better protected from extreme events, and thus are overall more resilient to climate change. This paper reviews the evidence demonstrating greater resilience on farms that maximize diversity, build soil organic matter, and incorporate other agroecological or ‘sustainable’ practices. We then discuss the current water crisis in California in the context of the vulnerability of our current agricultural systems to climate change, highlighting this as an opportunity to redirect agricultural policies and economic incentives. The projected increase in the frequency and intensity of climate extremes calls for policies that are concerned not only with present crises, but that also encourage a new culture of forward-thinking practices around land and water use. We highlight France’s new Law for the Future of Agriculture, Food and Forestry as an example of national policy supporting agroecology. Applying an agroecological approach to increase resilience will enable the U.S. to tackle the twin challenges of food production and increasing climatic unpredictability.

An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning

Abstract In the MTO (Make-To-Order) and MTS (Make-To-Stock) mixed production environment, it is important to make an accurate delivery promise on the ordering stage because the customer’s demand with unmatched production capacity is not always satisfied. A quick order promising method for an iron and steel enterprise, based on short-term production capacity balancing planning is proposed in this paper. With the help of this method, ATP (Available-To-Promise) concept is extended to RATP (Resource-Available-To-Promise) and DTP (Delivery-To-Promise) is given while making the resource promise. A heuristic method is developed to match the available resources with the order demand and the actual data testing results have shown that the method proposed can meet the demand of online order promising in a relatively short time.

Ensemble-Based Multiobjective Optimization of On/Off Control Devices Under Geological Uncertainty

Summary We consider robust ensemble-based (EnOpt) multiobjective production optimization of on/off inflow-control devices (ICDs) for a sector model inspired by a real-field case. The use of on/off valves as optimization variables leads to a discrete control problem. We propose a reparameterization of such discrete controls in terms of switching times (i.e., we optimize the time at which a particular valve is either open or closed). This transforms the discrete control problem into a continuous control problem that can be efficiently handled with the EnOpt method. In addition, this leads to a significant reduction in the number of controls that is expected to be beneficial for gradient quality when using approximate gradients. We consider an ensemble of sector models where the uncertainty is described by different permeability, porosity, net/gross ratios, and initial water-saturation fields. The controls are the ICD settings over time in the three horizontal injection wells, with approximately 15 ICDs per well. Different optimized strategies resulting from different initial strategies were compared. We achieved a mean 4.2% increase in expected net present value (NPV) at a 10% discount rate compared with a traditional pressure-maintenance strategy. Next, we performed a sequential biobjective optimization and achieved an increase of 9.2% in the secondary objective (25% discounted NPV to emphasize short-term production gains) for a minimal decrease of 1% in the primary objective (0% discounted NPV to emphasize long-term recovery gains), as averaged over the 100 geological realizations. The work flow was repeated for alternative numbers of ICDs, showing that having fewer control options lowers the expected value for this particular case. The results demonstrate that ensemble-based optimization work flows are able to produce improved robust recovery strategies for realistic field-sector models against acceptable computational cost.