Metal casting is one of the most basic yet most useful manufacturing methods available to designers. These processes involve pouring molten metal inside of a preformed mold, which becomes a finalized part when cooled. The ability to shape metal without the need for machining has allowed for the mass production of complex parts that are both durable and inexpensive. As a result, there are many processes used to cast metal, and this article will highlight the most widely used casting method, sand casting. This process uses sand to create any number of complex mold shapes, and this article will show how this process works, how it fares against other methods, and where sand casting is used in industry today.
Sand casting is a casting process by which sand is used to create a mold, after which liquid metal is poured into this mold to create a part. To learn about the other forms of casting, visit our article on the types of casting processes. Sand is used in this method because it insulates well, it is relatively cheap, and it can be formed into any number of mold shapes. There are defined steps to this process (shown simplified in Figure 1), and this article will walk through each of these steps to illustrate exactly how this casting procedure is conducted.
The first step in the sand casting process involves fabricating the foundry pattern - the replica of the exterior of the casting - for the mold. These patterns are often made from materials such as wood or plastic and are oversized to allow the cast metal to shrink when cooling. They are used to create the sand mold for the final part, and can potentially be reused depending upon the pattern material. Often times, two pattern halves are separately created which provides cavities when put together (shown in Figure 1). Cores are internal mold inserts that can also be used if interior contours are needed, but are typically disposable after one casting. The type of pattern and its material is dictated not only by the desired part dimensions but also by the number of castings needed from each mold.
The second step is the process of making the sand mold(s) from these patterns. The sand mold is usually done in two halves, where one side of the mold is made with one pattern and another side is made using the other pattern (shown in Figure 1). While the molds may not always be in two halves, this arrangement provides the easiest method of both creating the mold and accessing the part, once cast. The top part of the mold is known as the cope and the bottom half is the drag, and both are made by packing sand into a container (a flask) around the patterns. The operator must firmly pack (or ram) the sand into each pattern to ensure there is no loose sand, and this can be done either by hand or by machine. After ramming, the patterns are removed and leave their exterior contours in the sand, where manufacturers can then create channels and connections (known as gates/runners) into the drag and a funnel in the cope (known as a sprue). These gates/runners and sprues are necessary for an accurate casting, as the runners and gates allow the metal to enter every part of the mold while the sprue allows for easy pouring into the mold.
The third main step in sand casting is clamping the drag and cope together, making a complete mold. If a core is needed for some internal contours, it would be placed into the mold before the clamping step, and any gating/runners are also checked for misalignments.
The fourth step begins when the desired final material (almost exclusively some metal) is melted in a furnace, and is then poured into the mold. It is carefully poured/ladled into the sprue of the mold, where the molten metal will conform to the cavity left by the patterns, and then left to cool completely. After the metal is no longer hot, manufacturers will remove the sand from the mold (via vibrations, waterjets, and other non-destructive means, known as shakeout) to reveal the rough final part.
The fifth and final step (not shown in Figure 1) is the cleaning step, where the rough part is refined to its final shape. This cleaning includes removing the gating system and runners, as well as any residual mold/core parts the remains in the final piece. The part is trimmed in areas of excess, and the surface of the casting can be sanded/polished to a desired finish. After major cleaning, each part is inspected for defects and is tested to ensure compliance with the manufacturers standards of quality, so that they will perform as intended in their respective applications.
The sand casting process has numerous advantages, especially over investment casting, another popular casting method (to learn more, read our article all about investment casting). This section will briefly explore why sand casting is so widely distributed in industry, as well as where it falls short as a manufacturing method.
So while sand casting may be a cheaper alternative to investment casting and can provide much more complex shapes, it takes a lot more legwork to get the same accuracy, finish, and overall part quality.
It is difficult to grasp how many different technologies use sand casting. Its versatility as a casting process makes it ideal for almost any complex part, and almost every modern technology benefits from this manufacturing process. Below is a list of only a few of the products which are fabricated using the sand casting process, which shows just how varied the possible applications can be.
Sand casting, while nowhere near as precise as investment casting, is a low-cost, low complexity manufacturing process that has repeatedly proven itself as an integral part of modern manufacturing. If investment casting is too cumbersome, or if large parts are needed, consider implementing sand casting into your production line.
This article presented a brief overview of the sand casting process. For information on other products, consult our additional guides or visit the Thomas Supplier Discovery Platform to locate potential sources of supply or view details on specific products.
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The production system of an organization is that part, which produces products of an organization. It is that activity whereby resources, flowing within a defined system, are combined and transformed in a controlled manner to add value in accordance with the policies communicated by management. A simplified production system is shown above.The production system has the following characteristics:
JOB SHOP PRODUCTION Job shop production are characterized by manufacturing of one or few quantity of products designed and produced as per the specification of customers within prefixed time and cost. The distinguishing feature of this is low volume and high variety of products.
BATCH PRODUCTION Batch production is defined by American Production and Inventory Control Society (APICS) as a form of manufacturing in which the job passes through the functional departments in lots or batches and each lot may have a different routing.It is characterized by the manufacture of limited number of products produced at regular intervals and stocked awaiting sales.
MASS PRODUCTION Manufacture of discrete parts or assemblies using a continuous process are called mass production. This production system is justified by very large volume of production. The machines are arranged in a line or product layout. Product and process standardization exists and all outputs follow the same path.
CONTINUOUS PRODUCTION Production facilities are arranged as per the sequence of production operations from the first operations to the finished product. The items are made to flow through the sequence of operations through material handling devices such as conveyors, transfer devices, etc.
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The concept of lean manufacturing was developed for maximizing the resource utilization through minimization of waste, later on lean was formulated in response to the fluctuating and competitive business environment. Due to rapidly changing business environment the organizations are forced to face challenges and complexities. Any organization whether manufacturing or service oriented to survive may ultimately depend on its ability to systematically and continuously respond to these changes for enhancing the product value. Therefore value adding process is necessary to achieve this perfection; hence implementing a lean manufacturing system is becoming a core competency for any type of organizations to sustain. The majority of the study focuses on single aspect of lean element, only very few focuses on more than one aspect of lean elements, but for the successful implementation of lean the organisation had to focuses on all the aspects such as Value Stream Mapping (VSM),Cellular Manufacturing (CM), U-line system, Line Balancing, Inventory control, Single Minute Exchange of Dies (SMED), Pull System, Kanban, Production Levelling etc., In this paper, an attempt has been made to develop a lean route map for the organization to implement the lean manufacturing system. Analyses of the exploratory survey results are summarized in this paper to illustrate the implementation sequence of lean elements in volatile business environment and the finding of this review was synthesized to develop a unified theory for implementation of lean elements.
Commonly referred to as Industry 4.0, the adoption of modern-day technology, much of it smart technology, to enhance every aspect of business and make many of todays industrial systems autonomous is no longer viewed as a marketing pitch but a reality that is changing the way companies operate.
There are 16 technological advancements that have helped usher in a new modernization of industrial manufacturing and created an irrevocable change in the way businesses produce their goods and compete within their given industry.
As far as manufacturing is concerned, 5G will change the traditional role of wireless communication as the formerly limited connectivity that most plants, factories, and warehouses experienced in the past will now be a thing of the past.
Again, as 5G will supply a more consistent and constant Internet connection, production lines and manufacturing plants will employ more and more modern technology which uses IoT to make their systems faster, more efficient, and more secure.
Faster speeds, lower latency levels, and a massive communication network will not only to change industries and production processes & capabilities but also the entire economic potential of countries around the globe.
Massive amounts of inventory, many assembly-line employees and various inspectors and technicians are all packed into one large production center trying their best to get everything organized and moving ahead as scheduled.
Mobile apps can help bridge the gap between time and space in such facilities by integrating with CRM software, the result of which is constant communication between customers and plant workers, managers, and officials, making it easier to process orders in a more timely and flexible manner.
All you need to do is to input the mockup manufacturing data into your app via your smartphone or tablet and it will immediately relay the information to the IoT equipment at the production plant where production will start immediately.
Industry 4.0 and the Internet of things (IoT) have become phrases we use simultaneously to reference the impact technology is having on modern-day industries but also the impact smart technology is having on manufacturing.
As all the robots, tools, and devices which make up these nine core technologies have sensors and data processing & collection capabilities, we can connect them via IoT technology and bring them together in a harmonious loop.
Although IoT and IIoT refer to the same technology, it should be clear that the term IoT refers to consumer goods and IIoT (Industrial Internet of Things) for industrial processes such as manufacturing.
Harley Davidson, originally found it very difficult to retrofit their IIoT sensors within their manufacturing plant but could cut down their build-to-order cycle and increase productivity by 3-4% once their fully-functional IoT production facility was completed.
As a manufacturing plant is an environment where we need real-time data as quickly as possible to ensure efficiency and safety, the ability to wear technology that can alert an employee of relevant information is invaluable.
Not only can such technology provide constant comfort for production line and manufacturing plant workers but can also detect dangerous levels of heat and cold and therefore protect the user from potential harm.
Many big-name brands already use the above wearables to increase productivity and promote worker safety within their plants but BMW has taken this technology a step further with the unveiling of their new virtual factory where quality controllers can point to any part of the factory and analyze & document flaws through the use of a wearable.
The main benefit of such techniques is that a maintenance crew does not have to wait until a machine breaks to fix it, as they can make minor adjustments before a major problem occurs, especially during planned downtimes which almost always requires lower costs.
Incorporating such technology within a manufacturing facility to improve predictive maintenance has increases ROI by tenfold, reduce maintenance costs by 30%, reduce downtime by 35-45%, and decrease equipment breakdowns by over 70%.
We have discussed already much about the predictive maintenance aspect of Industry 4.0 but another benefit that this technological revolution is having on manufacturing plants worldwide comes in the form of predictive quality and safety through machine analytics.
Once a machine understands that the quality of a product is about to enter a downward spiral through analyzing product data it has collected, it can halt the production of such products and offer solutions before restarting it again.
Supervised Machine Learning: Here the target is already defined input and output data & the desired outcome is known. The only thing the machine needs to do is match the two to come up with the necessary prediction for the desired scenario.
A great example of machine learning in action is Siemens; a German conglomerate, use of machine learning in the form of neural networks unsupervised machine learning to both monitor and improve its steel plant efficiency.
Siemens says that its investments in machine learning networks are the main reason it could improve its gas turbine emissions to the degree it has better than any human could have done, according to the conglomerate.
The company continues to invest in machine learning and AI technology to improve its manufacturing facilities and says it will continue to add upon the $10 billion it has already invested in US software companies over the last decade.
The old way of processing, analyzing, and optimizing manufacturing data is now irrelevant with Industry 4.0 technology. It can not keep up, let alone scale-up, with the ever-increasing amounts of data smart machines can collect and store.
Cognitive technologies, which are built upon the foundation of IoT, can fully use massive amounts of data across many systems, processes, and equipment to come up with insights into the entire supply chain beginning with design and ending with customer support.
What they found was that many of the electronic companies were already using cognitive manufacturing technologies in full swing and were actually experiencing greater ROI due to higher productivity levels by using such technologies.
Hybrid manufacturing refers to the combination of two technologies working in unison within a manufacturing setting, namely additive manufacturing (i.e., 3D Printing) and subtractive manufacturing (i.e., Computer Numerical Control CNC milling).
The main benefit of using both these technologies together is a more unified and precise manufacturing environment where greater design freedom can efficiently and create intricate and flexible parts no matter how complicated or radical their designs may be.
Distributed ledgers are comprised of databases which are spread throughout a broad range of locations to make transaction transparency clearer and so make it very difficult for cyber attacks to occur as each transaction is publicly witnessed throughout a synchronized network.
Fujitsu, a Japanese IT company, believes IOTA blockchain technology will be the missing piece that will link the various Industry 4.0 technologies together and play an integral part in the creation of the smart factories of the future.
As many of the traditional BI tools helped in creating predictive measures for the situations described above, they can not spot quality defects in real-time and offer solutions to the design team to rectify them.
Industry 4.0 technology, specifically IoT and integrated data systems, have made this chain more holistic and managing it much easier with constant information being bounced back-and-forth from department to department so that one departments decision-making does not affect another part of the supply chain adversely.
Between 2007 to 2016, Home Depot unified each of its stores logistics management departments into one centralized unit as their workers were more busy managing and replenishing inventory than helping customers.
Machine to Machine (M2M) communication is the collection of data from machinery via electronic sensors to the transference of such data via networks to special software that can accurately interpret it.
The transference of data between machines and software either becomes the product of human evaluation or direct imperatives that are transferred directly to other machines and processes in order for them to complete their tasks.
M2M method and technology are the cornerstones of Manufacturing 4.0 as the amount of data collected in todays manufacturing facilities are often too large to interpret using traditional data collection and analysis methods & tools.
Manufacturing machines have not only the ability to collect massive amounts of data but also can store, transfer, and interpret such data so humans can make sense of it and use it to improve the production process.
Traditionally, M2M communication was a product of hard-wired networks, which limited both the amount of data processed and data processing speed because of close network proximity and lack of protocols.
Also, advanced machine sensory equipment and software has connected floor operation with office management and allowed them both to access and transfer data simultaneously in real-time which helps the entire production line keep track with recent market conditions.
As machines can now automatically collect, monitor, and interpret data, and decide and adjustments by themselves, production workers are left with extra time to come up with better product designs, processes, and systems.
Artificial intelligence, also referred to as machine learning, in a manufacturing setting includes smart tools like pattern-recognition software and robots that use sensors to collect data for analysis.
Such AI technology, however, is not solely limited to robots and other production machines as the smart factories of today are already using various AI technology within their production processes, manufacturing systems, and other tasks that are not linked directly to the production line.
As AI technology is not just capable of collecting but also combining data from every process and machine within a production facility, it can use and correlate such massive amounts of various data to reduce yield detraction.
Cyber-Physical Systems (CPS) refers to the bridging of the physical world with computing & communication technology. The systems themselves are monitored and controlled by computer algorithms and are connected to end-users via the Internet.
The main advantage of CPS, or cyber manufacturing, has over traditional manufacturing management systems (e.g., experience-based management systems) is that it relies entirely on evidence to keep the real-world and digital-world connected to manage assets and assess risks and opportunities.
While many manufacturers cite the fact they have a lack of trained cybersecurity staff and the budget to hire them, there are various low-cost and easy-to-implement security measures that can help keep sensitive data safe.
These technologies and systems have interconnected the entire production line, from start to finish, in such a way that massive amounts of data from various sources and departments can now be used by any member or team within a manufacturing facility to communicate and analyze information in a virtual environment and then translate it back into real-world applications.
From a contract manufacturing firm, BuntyLLC evolved into a full service custom machined, forged and cast metal parts fabrication enterprise. We supply global solutions from our headquarters in Greenville, South Carolina.