Steel productionThere are many legacy techniques still being applied to the design of large organizations and capital intensive installations such as factories. Often these are driven by tradition or accounting practice rather than customer focus or operational effectiveness. For example it's not uncommon to find guidelines requiring the highest possible utilization of the most expensive piece of equipment, such as a welding robot for example. This is meant to amortize the cost of the capital expenditure associated with the robot driving down its why per-unit cost. But with accounting strategies such as this can actually have an overall negative effect on the bottom-line. For example this robot, running continually, will increase the material supply cost upstream of its location and may far exceed the downstream operation's input capacity. This creates a great deal of work-in-progress inventory, drives material handling and storing costs up as half completed pieces are shoulder on the factory, and may even require a floor plan expansion. Robot output has increased, but factory output has stayed the same while factory costs have increased. Not a good scenario.

Real-world operations have several levels of complexity: multiple production lines, competition for resources, hidden costs, and so on. Traditional process redesign techniques often simplify a complex process but usually falls far short of optimizing it. There are simply too many interacting variables and ripple effects. A suggested improvement may appear elegant on paper but have significant unintended consequences buried deep within. We face this situation every day.

Our partners tackle this challenge via simulation modeling. Following a data gathering and assessment stage, they design a simulation model that will give the experimenter the scope to consider all planned modifications, assess their effectiveness, and make any necessary corrections prior to the start of implementation.

Typical manufacturing problems that our partners solve are: Manufacturing Expansion, Increasing Output, Reducing Production Cycle Time, Improving Equipment Utilization, Materials Analysis and Volume Optimization.

Please visit our models gallery to review different industrial examples.

Case Studies

  • GE Manufacturing Plant Uses AnyLogic for Real Time Decision Support
    In 2012, GE opened a new battery manufacturing plant in conjunction with the launch of an innovative energy storage business. GE’s exciting opportunity brought on many new challenges, such as increasing production throughput and yield under evolving processes and uncertainties, and reducing manufacturing costs in order to gain market share. The GE Global Research Center sought out a powerful and flexible tool to analyze, not just the specific process, but the manufacturing system as a whole.
  • Shipyard Capacity Analysis
    With AnyLogic simulation software as the centerpiece, NASSCO utilizes a custom-built analysis system called the Large Scale Computer Simulation Modeling System for Shipbuilding (LSMSe) to provide highly detailed and accurate capacity analyses for both current production and potential new work.
  • Production Planning in Marine Industry
    The managers of one of the most important Italian yacht manufacturers needed a new, intelligent approach that would make the planning process simpler. The objective was to give the real production planner exceptionally rich planning information, which would allow the person to test and refine a plan before its implementation.
  • Simulating Ice Cream Production: Recognizing Constraints and Optimizing Production Plan
    Conaprole, the biggest dairy production company in Uruguay, produces more than 150 SKUs in their ice cream plant, using five production lines, and up to five different packaging configurations for each line. The management’s challenge was to be able to reformulate their plans in order to balance supply and demand and make sure they would avoid stock-outs in key products. They also sought ways to optimize the use of their production capacities.
  • Simple Simulation Model Helps Intel Avoid Production Plant Downtime
    Intel factories used a particular type of equipment that often broke down, which caused capacity constraints. These expensive parts were used in critical factory operations, and the repairs took significant time, so it was necessary to have extra spare parts on hand to avoid downtimes. Broken parts caused constraints at some of the factories while other factories over purchased spares.
  • Improving Mining Outbound Logistics with Agent-Based Simulation Modeling
    One of the largest resource companies in the world, with over $80 billion in sales, decided to enter a new market. It was planning to build a new potash mine with 90% of the resources exported. They wanted to design a reliable supply chain, with a high speed of supply replenishing, and the ability to recover from natural disasters and man-made crises benefiting from such volatility. Amalgama and Goldratt companies contracted this project to design the potash mining operations and a full supply chain of outbound logistics.
  • Modeling and Optimization of Oil Production Using AnyLogic Fluid Library
    Canada is the third largest country to have oil reserves. However, most of the oil is in oil sand – the mixture of sand, oil, and water – which has to be heated up with steam to emit the oil. It is costly to maintain such a distribution system, and outages may lead to disruptions in steam injection and oil production. Stream Systems company applied AnyLogic simulation modeling to optimize expenditures and capture production lags
  • Highly Automated Production Line Planning and Optimization
    Centrotherm Photovoltaics AG is a global supplier of technology and equipment for the photovoltaics, semiconductor, and microelectronics industries. The company needed to identify the best automated production line and factory configuration to minimize costs and maximize throughput and reliability.
  • Simulation of the Construction of a Tunnel with a Tunnel Boring Machine
    The cost of one hour of down time of a tunnel boring machine is usually high and project managers have to do their best to avoid unnecessary delays in construction. The aim of the simulation project, which was carried out at Ruhr University Bochum in Germany, was to create a simulation model that would be capable of determining the bottlenecks in tunnel building processes in order to minimize the possible monetary losses.
  • Shipyard Proves Order Fulfillment Capability and Gains Visibility into Production Facility and Distribution
    Faced with a large order for diesel powered submarines, Admiralty Shipyards JSC must evaluate whether the current production facilities can fulfill the order, and if not, what amount can be produced by the year 2016. Admiralty Shipyards JSC is also seeking confirmation that an additional production facility will not be needed to complete the order.