Manufacturing

This paper presents a closed loop supply chain for a reusable, deteriorating tool. The tool is used in a manufacturing process on an item in a linear supply chain. A model is created for the linear item supply chain and the tools closed loop supply chain to analyse the interactions between them and various input parameters so that output responses of the system can be modelled. Three approaches are taken to model the system, a brute force factorial design, a modified version of a Latin hypercube space filling design, and a fast flexible space filling design. It is found that all three methods Design Expert, RLHC, and FFFD, accurately predict the response with the least amount of input. Space filling designs should be used if more factors are needed as they minimise the total amount of simulations needed to produce an accurate model.

A master thesis within mechanical engineering performed by two students has been conducted at Scania in Oskarshamn. The purpose has been to investigate if Discrete Event Simulation using ExtendSim can be applied to increase Scania's assembly productivity. The objective was to investigate how buffer systems could be managed by varying the amount of buffers and their transport speed. Assembly line takt times with regard of their availability was also investigated. The method of approach was to build a simulation model to gain valid decision making information regarding these aspects. Process stop data was extracted and imported to ExtendSim where the Reliability library was used to generate shutdowns.

Comparing 24 sets over 100 runs to each other a median standard deviation of 0,91 % was achieved. Comparing the total amount of assembled cabs over a time period of five weeks with the real time data a difference of 4,77 % was achieved. A difference of 1,85 % in total amount of shutdown time was also achieved for the same conditions.

The biggest effect of varying buffer spaces was for system 6A. An increasement of up to 20 more assembled cabs over a time period of five weeks could then be achieved. By increasing all the buffer transport speeds by 40 %, up to 20 more assembled cabs over a time period of five weeks could be achieved. A push and pull system was also investigated where the push generated the best results. A 22 hour decreasement of total shutdown time and an increasement of 113 more assembled cabs over a time period of five weeks could be achieved.

This project establishes a Closed-Loop Supply Chain (CLSC) design that is analysed through a series of simulation models, aimed at defining the highest performing production control strategy, whilst considering multiple related variables on both the forward and reverse flow of materials in manufacturing environments. Due to its stochastic nature, the reverse logistics side of the CLSC represents an increased source of variance for the inventory management and control strategies as it implies the erratic supply of returned materials, in addition to the very random customer demand, hence with highly variable inputs on both sides of the productive system, intrinsically inherent to this line of research. The dynamic allocation policies, particularly the Dynamic Hybrid Extended Kanban CONWIP special case (DNC HEKC-II), throughout the research space in consideration, evidenced very superior production control performance overall.

Shipbuilding is one of the most complex existing manufacturing processes. The large number of operations necessary to produce the parts that make up a vessel coupled with the need to synchronize multiple workflows and numerous resources where serial production is practically non-existent, make the management of such a production system very difficult. Simulation is an extremely powerful tool for the decision-making process to test and evaluate different scenarios, to efficiently plan future investments, to determine the allocation of resources, and to drastically reduce the risks of making incorrect decisions. This case study uses ExtendSim to model the manufacturing process of a frigate from the shipyard of Navantia Ferr to minimize the uncertainties of shipbuilding.

In multiproduct manufacturing systems, it is difficult to assure that an optimised setting of a pull production control strategy will be able to maintain its service level and inventory control performances. This is because the competition for resources among products is liable to make them affect the service levels of one another. By comparing different pull strategies, research presented in this paper has observed that tightly coupled strategies are able to maintain lower amount of inventory than decoupled strategies, but they do so at the detriment of service level robustness. As a result, tightly coupled strategies are better suited to manufacturing environments with low variability, while decoupled strategies are more robust in high variability environments. Here, robustness is a measure of how well a strategy is able to minimise the drop below its original optimised service level when the initial system conditions change. Furthermore, the Kanban allocation policy applied under a strategy plays a major role in its ability to manage the performances of multiple products. Experimental results show that the Shared Kanban Allocation Policy (SKAP) keeps a lower amount of inventory than the Dedicated Kanban Allocation Policy (DKAP), but it is more susceptible to the variability in the demand or processing times of one product impacting the service level of another. Therefore, a Hybrid Kanban allocation policy (HKAP) that combines both the DKAP and the SKAP has been implemented. This approach considers products’ demand and processing time attributes before categorising them into the same Kanban sharing group. The results of the implementation of the HKAP show that it can keep as low inventory as the SKAP and avoid products impacting the service levels of one another. Additionally, it offers a better approach to managing large multiproduct systems, as the performances of product groups can be differentially managed through the combination of Kanban sharing and dedication policies. Lastly, the observations on the performances of strategies and policies under different system conditions can be used as a framework through which line designers select strategies and policies to suit their manufacturing system.

Designing a casthouse for billet is a complex activity. The billet casthouse must be properly sized to optimize the metal flow, and continuously feed the homogenization shop, while bearing in mind that oversizing adds no value and is costly. To solve this problem, it is necessary to accurately analyze the operations of the casthouse in real time and this requires a discrete simulation model.

Gwenola Jaouen of Rio Tinto Alcan Smelter Technology in Voreppe Cedex, France developed an ExtendSim model containing a library that includes all the necessary equipment: conveyors, continuous and batch furnaces, and finishing stations. The model was used to design an expended casthouse which requests the management of complex product mixes and which challenges the robustness and flexibility of the installation. By combining this model with the metal flow sizing model, it was possible to validate the performance of the design and its impact on casthouse operation. This resulted in a shop designed for customer needs, at optimal cost.

Project details were presented at TMS (The Minerals, Metals and Materials Society) 2011 Annual Meeting & Exhibition in March of 2011 at the San Diego Convention Center, San Diego, California.

Variability in production is one of the largest factors that negatively impacts construction project performance. A common construction practice to protect production systems from variability is the use of buffers (Bf). Construction practitioners and researchers have proposed buffering approaches for different production situations, but these approaches have faced practical limitations in their application.

In Multiobjective Design of Work-In-Process Buffer for Scheduling Repetitive Building Projects, a multiobjective analytic model (MAM) is proposed to develop a graphical solution for the design of Work-In-Process (WIP) Bf in order to overcome these practical limitations to Bf application, being demonstrated through the scheduling of repetitive building projects. Multiobjective analytic modeling is based on Simulation–Optimization (SO) modeling and Pareto Fronts concepts. Simulation–Optimization framework uses Evolutionary Strategies (ES) as the optimization search approach, which allows for the design of optimum WIP Bf sizes by optimizing different project objectives (e.g., project cost, time and productivity). The framework is tested and validated on two repetitive building projects. The SO framework is then generalized through Pareto Front concepts, allowing for the development of the MAM as nomographs for practical use. The application advantages of the MAM are shown through a project scheduling example. Results demonstrate project performance improvements and a more efficient and practical design of WIP Bf. Additionally, production strategies based on WIP Bf and lean production principles in construction are discussed.

Brief introductory article discussing the key element in lean implementation: simulation. Simulation has been used successfully in factory floor improvement, inventory management, capacity analyses, and process design. Benefits such as the following are not unusual.

• Postponing final packaging results in 30 percent inventory reduction with substantial service improvement to more than 97 percent.
• Shift/work center change allows reduction of staff from 7 to 6 days per week.
• Adding staff to a bottleneck work center reduces overall number of workers by 10 percent.
• Synchronized operations reduce cycle time from 18 to 13 weeks.

This paper presents a case study where simulation was used to convert from a manufacturing resource planning (MRP) based push process to a demand-driven pull process in a single plant operation factory floor. Simulation is a software program that allows one to visually see and measure how processes perform over time, including materials, information and financial flows, and how probabilistic variables impact them

Procter & Gamble partnered with the Energy Department's Los Alamos National Laboratory (LANL) in the 1990s. LANL scientists helped P&G engineers develop simulations to improve the reliability of P&G's complex production lines. P&G's 150 facilities worldwide saw a 44 percent increase in plant productivity and 30 percent increase in equipment reliability since they started using the software.

The pairing of the lab and corporations' data led to the creation of simulation software called Reliability Technology in 1993. With the software, engineers can configure both the machines and their maintenance schedules based on reliability. In addition, engineers could foresee and possibly avoids product jams, intervals of a component breakage or variations in a machine speeds. In other cases, engineers could triage the production line. Large-scale implementation of the technology helped save P&G $1 billion in manufacturing costs, according to Procter & Gamble. These cost-saving benefits are applicable towards production lines across the manufacturing sector.

LED (Light Emitting Diode) has many excellent features as a new lighting device and has been widely used by far. The structure and light-emitting principles are introduced in this paper. The LED manufacturing process is explained and shown dynamically. A processing line is modeled and simulated in ExtendSim. The simulation result is analyzed and the processing line is balanced. Throughput is improved with the simulation.

"Some years ago I walked into a PCB facility that was making very complex HDI product, but wasn’t making any money. By focusing on constraining the WIP (CONWIP), identifying and focusing on the production bottlenecks to help develop a scheduling paradigm, working side by side with the operators to devise their own rules for dispatching jobs, and implementing a production pull system using Kanbans, profitability soared, WIP was reduced by two-thirds, and the standard production lead time decreased from 15 to four days with one-day quick-turns."

Logic and assumptions used in building a simulation model of an Automated Material Handling System (AMHS) for an eight inch Wafer FAB are presented in this paper. The ExtendSim model built for this project includes the ability to make changes to the area stocker layout, number of area stockers, number of loops, number of cars, and/or the number of Lot moves. This model is used to determine if the Area Stockers can handle the quantities of Lots per hour required by From-To-Table "customer" requirements.

Packages that accurately emulate the hybrid processes that characterize food and beverage manufacturing are making simulation more than just a snazzy presentation tool for upper management. Virtual Engineering's New Frontier describes users roughing out their production and packaging lines on screen to gain insight into the dynamics of their lines and where and why bottlenecks occur.