Semiconductors are extremely complex microchips that help power the vast array of technology that surrounds us every day. As integrated circuits have decreased in size, they have grown in complexity, introducing new manufacturing challenges and making workflow management a critical component in the design and manufacturing process.
The earliest use of software in semiconductor creation was Computer-Aided Design (CAD), which gave designers a way to layout circuitry more efficiently by using computer drafting tools. This was followed by Computer-Aided Engineering (CAE) and the first simulation programs which allowed engineers to save money by emulating how their circuits would function without having to build them. As technology advanced, using computer programs to design and simulate semiconductors became a standard best practice, and the umbrella term Electronic Design Automation (EDA) was created.
Given the increasing complexity of integrated circuits, the smaller size requires extreme precision during design and manufacturing. This precision comes with a high price tag which makes the cost-controlling benefits of EDA even more important. However, EDA on its own is not enough to succeed in this competitive market. Companies also need to leverage Artificial Intelligence (AI) and Machine Learning (ML) to observe and optimize activities such as job queues by using data to build models based on server activity and resource usage that will adjust job runtimes to eliminate unused license time and reduce cost.
Despite all these solutions and advancements, no one company has the ability to create complex computer chips. They must collaborate with supply chain, IP providers, and other third-party partners. As you can see, companies are under a lot of pressure to reduce costs and time-to-market while navigating a wide variety of software programs and partnerships. The chip design process is highly iterative and the chip manufacturing process is exacting. Leveraging a software solution to help track these diverse workflows is required for semiconductor companies to succeed in today’s competitive industry.
Workflow management is the process of designing, creating, executing, and monitoring workflows – and improving them based on observations and data. Computer chip design has many steps and dependencies across different companies. Therefore, many workflows are required to track everyone’s work in order to maintain a clear picture of the product status, and workflows must be optimized for efficiency and to ensure precision and quality.
Any time you’re working on a project with a lot of moving pieces and multiple stakeholders it’s important to create and communicate processes to support everyone’s work. Including all stakeholders in this part of the process can help uncover any gaps, redundancies, or bottlenecks and teams can work together to identify what changes would be the most beneficial for the overall project. This collaboration can increase transparency, improve communication, and result in streamlined tasks. Once standardized across teams, workflow management provides employees with clear expectations that helps hold them accountable.
As you’re building or refining your processes, it can be helpful to visualize them. To successfully map a workflow you must fully understand your process and all the possible outcomes. Once you have your workflow mapped out, the high level view can be used to narrow down areas for improvement or identify areas that require further investigation and analysis.
Of course, building, mapping, documenting, and improving workflows by hand would be almost impossible for something as complex as a semiconductor. This is why EDA is so widely used in the computer chip industry. No matter what phase of design or development, software tools can help optimize workflow management by giving teams the tools to document, reuse, and refine processes.
In addition to optimizing the creation and mapping of processes, workflow management is used to identify areas for automation to gain further efficiencies. Once processes are clearly defined and repeatable, it is easier to identify which tasks can be automated. Companies should also leverage AI/ML to get the most cost savings from automation. This McKinsey article takes a deeper look at the potential of AI to create value in the semiconductor industry.
Well defined processes that are mapped, optimized, and tracked and automated using software solutions all contribute to scalability. With clear instructions that aren’t full of unnecessary tasks, designers and engineers are able to complete processes more quickly. By leveraging AI/ML and automation, your designers and engineers can focus on the tasks where they have the most impact, helping them scale to work on larger projects.
The potential of workflow management to improve your overall progress is promising, but having to navigate multiple software solutions for the different areas of chip design and manufacturing can introduce confusion and inefficiencies into your processes. One way to improve your semiconductor software is by investing in a tool that supports unified product design and development. Digital Engineering explains that, “you need to integrate all the tools of the trade as well as all product development participants on an open, centralized platform that supports (and encourages) cross-disciplinary collaboration while managing data.”
Perforce does that by bringing together design, development, IP management, traceability, and data management into one platform that supports secure collaboration.
Perforce leverages Methodics IPLM for IP Lifecycle Management. Methodics IPLM includes features that support a traceable IP ecosystem, rapid workspace creation, hierarchical bill of materials, customizable dashboards, release automation, and enterprise-grade security that will take your team through the acquisition, qualification, distribution, and integration phases of the IP lifecycle.
Methodics IPLM is a unique single system solution for the semiconductor industry, centering product lifecycle management (PLM) around IP while allowing companies to further tailor the solution to their needs. It also integrates into your existing PLM tool with a flexible API. The IP-centric approach encourages reuse, and you can use Helix Core, Git, and Methodics IPLM together as a seamless data management solution. This provides a single source of truth that scales to support complex products and remote team members.
Companies prefer to use their semiconductor design software with Helix Core because it allows developers to store and use large-size files containing IPs and chip design documents, all while accessing them from a centralized location.
Assembla has been hosting Perforce in the cloud longer than any other company and can take the technical overhead off your plate while providing world-class cloud-based semiconductor design software. With reliable redundancies, flexible storage, a stable infrastructure, better performance, and increased security, you can trust Assembla to host cloud-based SCM and SCH for your semiconductor company.
If you’re ready to try cloud-based virtual production with Perforce, start a free 14 day trial of Assembla. Our team would love to talk with you about how a cloud solution can meet your development needs.
