August 2023 Volume 5

FORGING RESEARCH

which cascades to other variables. Thus, building intelligence capabilities within the forging machine could open new avenues for autonomous machine self-adjustment to achieve optimal condition in real time.

Figure 2-2: Digital Twin Fundamental Technologies A generic digital twin architecture for manufacturing is shown in Fig. 2-3. The architecture is composed of four main units: physical shop, virtual shop, shop floor service system, and shop floor digital twin data [17]. During production, the physical system (PS) will generate real-time data and transmit them to the virtual system (VS), where simulation, evaluation, and optimization based on models will be carried out in real-time and generate orders to regulate the production in the PS whenever necessary. The shop floor service system provides services to support normal operation and evolution of the VS and PS. The shop floor digital twin data unit is where VS models and their operation mechanisms are built and updated. This unit also houses all algorithms and models.

Fig. 2-3 Complex interactions of parameters in forging [18]

2.2 Inherence variances in a forging production line As briefly discussed in the introduction section, all the subsystems in a forging line exhibit inherent variances/disturbances that directly influence the quality of the forgings and process economics. Figure 2-4 show some of the inherent variances.

Fig. 2-4. Inherent variances in a forging line

• Friction The friction between billet and die during a forging process is often crucial to the success of the forging operation. In order to maintain low and constant friction lubrication is used. It is very important to know the friction conditions vary during forging. Friction is described by the friction coefficient (Coulomb-friction) or by the friction factor [19]. When the forging production cycle runs continuously, the interface friction is bound to change due to a multitude of variables that may change in time and space. This eventually affects the surface quality of the final product. Various authors have studied and mentioned the use of friction control to achieve the desired surface quality of forged products. Controlling the friction facilitates the metal flow and this helps eliminate many resulting defects like folds, cracks, etc. The friction effect can be analyzed using FEA and to some level the necessary changes can be implemented in the process to achieve better surface quality. Due to unavoidable change in friction conditions, process monitoring that results in real-time adjustment of parameters that cause the friction to rapidly change is of paramount importance. • Temperature of die and work piece In warm and hot forging, temperature plays a vital role. Forging is performed at elevated temperatures to reduce forging load; however, the temperature should be controlled to achieve the desired

Fig 2-3 Digital twin-driven product manufacturing in shop floor [17]

2.2. Complex interactions of parameters in Forging There are numerous variables in forging. As shown in Fig 2-4 the interaction of these variables is complex. Process control issues in forging are further exacerbated by the brief forging cycle time: usually on the order of a few seconds. During the forging cycle, thermal-mechanical loads vary greatly. For example, dies will exhibit stress fluctuation with very high stress amplitudes, and dies are rapidly cooled and lubricated to avoid thermal softening. Thus, a slight change in the die cooling rate or lubricant film is bound to change thermal loading characteristics and friction conditions,

FIA MAGAZINE | AUGUST 2023 74