Content provided by Dassault Systemes
Some of the most innovative developments currently being delivered by automotive manufacturers include new drive technologies, autonomous driving and connected cars. Fulfilling the demand for innovative models relies on a flexible network of internal and external partners. Even though these networks are already well established, the potential for optimization is still significant.
The assembly line sets the pace in automotive manufacturing. At this point in the production chain, suppliers must deliver their products just in time (JIT) and just in sequence (JIS) for vehicles to be assembled as planned. Success is measured by the entire supply chain committing to deliver within tight turnaround times. The greater the time pressure at the end of the chain, the harder each individual element of the chain must work.
The challenges of in-house production
Many standard vehicle parts and components are mass-produced in high volumes. These parts are typically used in a modular format and can include cockpits, transmission and engine parts (or even complete engines), soft and convertible rooftops, among others.
When it comes to production planning, the capacity of each plant — including all production resources — must be carefully allocated as a lack of capacity can result in bottlenecks. Various methods are available for determining the effective capacity. Planning the shifts of machine operators is another important part; a lack of operators with the required skill will inevitably lead to reduced capacity.
Suppliers are also under pressure to deliver on time. Sufficient material stocks and time buffers can help suppliers meet their deadlines, but stock also represents tied-up capital. Coupled with high storage costs and limited containers to transport products at any one time, balancing stock inventories at the perfect minimum level is a tricky business.
So which option makes the most sense in production planning? Is it better to produce in advance, or schedule an additional shift later?
Planning requires several assumptions to become a reality
Another complication of production planning is the need to look after the actual production resources, tools and associated equipment. Any regular or unscheduled maintenance will always have an impact on production plans. Production controllers generally have differing responsibilities, analyzing and optimizing groups of machines in isolation rather than in conjunction with other machines or even plants in the chain.
It’s a common misconception that combining several optimized elements will automatically produce the ideal overall result. Once the decision is made to optimize one functional element, it is essential to look at the bigger picture and judge the effect of changes on any processes that take place before and afterwards. However, this level of transparency is often not available to production controllers and planners.
Ultimately, production controllers need a solution that either supports the planning process — or takes care of it automatically — by providing transparency for transmission plants, engine plants, tool manufacturers, press plants and other suppliers.
The key lies in transparency and integrated planning
The most important element of any planning solution is the ability for all dependent production steps to be planned in sync. A single production plan must therefore cover multiple production resources and assembly lines within a manufacturing plant, giving the planner full transparency and the freedom to plan beyond silos.
But that’s not all:
A planning solution of this nature must also visualize the actual production process while considering all relevant planning knowledge, rules and assumptions.
When the planner is unavailable, the solution must be able to help production teams make their own decisions in the face of disruptions or exceptional circumstances.
This planning solution must be able to propagate and display the effects of changes, decisions and disruptions in real time across all production steps, automatically checking the availability of all resources such as materials, containers and staff with the appropriate skills.
Whenever the production plan is adjusted, this solution must be able to evaluate scenarios in real-time based on planning KPIs. These evaluations identify added value that can be measured via various KPIs, thus allowing the success of any adjustments and the resulting scenarios to be quantified. In turn, these KPIs can be used to manage planning decisions and optimization efforts, thereby influencing how the plant performs in the future.
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