Business Decision-Making in the Factory of the Future. An IDC InfoBrief, Sponsored by Infor November 2015

Transcription

1 Business Decision-Making in the Factory of the Future November 2015

2 The manufacturing industry is on the threshold of a massive structural shift This shift is defined as: Industry 4.0 Factory of the Future Digital Manufacturing Smart Manufacturing Advanced Manufacturing Cyber/ Physical Manufacturing Manufacturing Renaissance Indeed, all these monikers are the same! pg 2

3 But how do manufacturers themselves define it? Manufacturers are really looking at the following characteristics, all of which are key attributes to future manufacturing: Agile Networked Automated These attributes, however, will necessitate a disruption in business models. pg 3

4 The long-term benefit The greater long-term benefit of the coming disruption will be the ability to manage processes in an autonomic or self-healing way i.e., capable of 4 automatically diagnosing and fixing inefficient or broken manufacturing processes. In the factory of the future, interconnected devices will be able to react autonomously to a broad range of internal or external events. Digitally enabled products and production lines will work in concert to reduce bottlenecks and proactively inform operators of available interventions to improve quality and increase throughput. 4 S.M.A.R.T. (SIMPLE, MODULAR, AGILE, RECYCLABLE, TIMESAVING) 4 NETWORKED 4 AGILE 4 AUTOMATED 4 DIGITAL 4 RESPONSIVE 4 LEAN 4 FAST 4 CONTINUOUS MINIATURE MODULAR PORTABLE pg 4

5 This future trajectory is about bringing together the operational and informational sides of manufacturing Today, the material flows of physical components and objects through the supply chain are separate from information flow. In the future, the broad convergence between information and operational technologies will remove the separation between products or materials and information, potentially in all processes and in all industries. One of the most striking examples could be that objects such as manufactured parts will become in a sense self-aware even when being produced. These products will analyze their own production status and quality, interact with the producing machine, and share this information with other machines or humans. pg 5

6 The opportunities of self-aware products and production WILL INCREASE 50% BY 2020 Given the huge opportunity of self-aware products and production, investments in foundational technologies enabling this new way of manufacturing such as Industrial Ethernet, Low Cost Sensors, Machine-Learning and Complex Event Processing, Data Historians, Manufacturing Intelligence, and Collaboration Tools. IN TERMS OF ADOPTION RATES, THIS MEANS THAT TODAY IDC SEES 15% OF COMPANIES BEGINNING TO PUT THE FOUNDATION TOGETHER FOR DIGITALLY-EXECUTED MANUFACTURING. THAT NUMBER WILL BE MORE THAN 65% BY pg 6

7 The shift to the 3rd Platform In past years, the industry has been shattered by massive technological transformations, moving from mainframe computing what IDC calls the 1st Platform to the PC- and client/server-based 2nd Platform. The industry is shifting quickly to the 3rd Platform, built on the foundations of mobility, cloud, Big Data analytics, and social business. New technologies such as Internet of Things, Collaborative Robotics, and 3D Printing, are emerging from this journey, and they are promising a completely new degree of business benefits all focused around improved agility and flexibility in manufacturing process. pg 7

8 The importance of blending old and new technologies Achieving the promise of the connected factory necessitates companies blending old and new technologies. Shop floor operational systems will need to communicate with enterprise applications that will most often be cloud and mobile-enabled supporting enterprise-wide analytics and decision making. While this transformation is revolutionary from the standpoint of business benefits, it still requires a step-by-step evolution in the technology adopted. Is industry 4.0 evolution or revolution? Traditional IT system Emerging IT technology Traditional machine Smart equipment Existing operating process Emerging business models Traditional IT architecture Cloud platform pg 8

9 The effect on operations How will this mashup between emerging 3rd platform architectures and supporting game-changing technologies work to support manufacturing operations? Today, companies are benefitting already from 3rd Platform technologies such as mobile, and cloud. Some technologies, such as mobile devices, gained a strong traction as they provided an invaluable tool to collect and deliver data to all relevant people on the shop floor. 74% of manufacturers are already experiencing a significant impact of these technologies. Is there an impact of these game changing technologies on the way manufacturing operations are managed today, in five years, and in ten years from now? Mobile devices Security Advanced data acquisition Cloud Big data analytics Additive manufacturing Social business and collaboration Advanced automation / robotics Digitally-executed manufacturing 0% 50% 100% n We are already experiencing an impact from this technology TODAY n We expect this to have an impact in the NEXT FIVE YEARS n We expect this to have an impact in TEN YEARS FROM NOW n No impact at all is expected Big data and analytics are often hyped, but manufacturers will begin to exploit the full power of data in the next few years. 90% of companies will have big data analytics capabilities. Indeed, data is the new oil in the manufacturing sector. pg 9

10 The interconnection of devices and the resulting data is becoming central to production and distribution 80% of companies say the main benefit from IoT technologies is the augmented visibility over operations and the resulting business speed, agility and cost reductions. Please outline in which areas you are leveraging or planning to leverage Internet of Things applications Production monitoring / visibility Quality control / management Remote maintenance and service Warehouse management Inventory management Remote production control Machine auto diagnosis Internal logistics management Remote machinery control Enable autonomous / self-healing production 0% 50% 100% n Currently in use n Not in use but planning investments over the next five years n Not in use and not planning pg 10

11 This digital transformation is led by non-it, C-level board members the CEO, CTO and COO CIO and shop floor LoB managers tend to be less involved This management shift is bringing up unprecedented challenges for the organizations. For the first time in history, these C-level executives are compelled to take an active role in strategic decisions on information technology matters. pg 11

12 Who wants to move first? Despite the amplitude of the transformation, today only a minority of companies wants to be a first-mover in developing these technologies The major barrier is the inability to create a consistent business case which in turns creates a lack of C-level commitment. Change management and integrating new technologies with existing ones are also obstacles. All in all, data and information are only useful to decision makers when they can actually take action and trigger new business processes. 35% Are keen on waiting to see changing technologies being proven in the industry first 5% Are completely risk-adverse, and not going to make any changes 23% Want to be the first movers in developing technologies 37% Want to be early adapters, but not first movers there may be risks... pg 12

13 ERP as a foundation for IoT ERP and SCM applications that provide seamless connectivity across a manufacturing organization are becoming the elective application for manufacturers to integrate many processes such as: Labor management Quality management Warehouse management Maintenance management Operations and detailed scheduling pg 13

14 Getting started with digital transformation IDC advises companies to leverage existing connectivity opportunities lying within always-cheaper sensors and mobile technologies, as well as previous investments in RFID This really entails starting with quick wins monitoring assets, for example, and leveraging these case studies as opportunities to develop the business case for larger investments within the organization. However, IoT technology and supporting applications such as integrated ERP can be also used to enable informationdriven workflows that range from very wide (e.g., machine failure, spare-part replacement) to much narrower in scope (e.g., quality checks). To do so, manufacturers must bridge the existing gaps between information and operations, and create an intelligence layer connecting the shop floor with the boardroom, providing real-time analytics to key decision makers. Today s technological landscape, which is making the creation and sharing of information continually easier and cheaper, is delivering ROI from these investments much faster because the impact of creating a single piece of critical information is amplified across the whole organization. pg 14

15 IDC Manufacturing Insights recommends the following» Converting raw data from the machine level into enterprise grade-information will transform and elevate the role of shop floors in manufacturing organizations and make them central in the fulfillment process.» This is a non-return step. The more information is made available, the more it will be requested from other business units.» Start from existing cloud initiatives in your organizations and adopt a trusted service partner to realize quick wins.» Consider the opportunities provided by technology to launching value-added initiatives (e.g. virtual centers of excellence to reconcile manufacturing performance across the plant floor network and distribute best practices).» Make a new contract with your employees, reorganize accountabilities allowing to unlock their full potential. pg 15